Implementing personalized medicine in a cancer center

Colorectal Tumors in Diverse Patient Populations Feature a Spectrum of Somatic Mutational Profiles

Admixed populations, including the Hispanic/Latino/a community, are underrepresented in cancer genetic/genomic studies. Leveraging the Latino Colorectal Cancer Consortium (LC3) and other existing datasets, we analyzed whole-exome sequencing data on tumor/normal pairs from 718 individuals with colorectal cancer to map somatic mutational features by ethnicity and genetic similarity. Global proportions of African, Asian, European, and Native American genetic ancestries were estimated using ADMIXTURE. Associations between these proportions and somatic mutational features were examined using logistic regression. APC, TP53, and KRAS were the top three mutated genes across all participants and in the subset of Latino individuals in LC3. In analyses examining recurrently mutated genes, tumors from patients of Latino ethnicity had fewer KRAS and PIK3CA mutations compared with tumors from non-Latino patients. Genetic ancestry overall was associated with CDC27 mutation status, and African genetic ancestry was associated with SMAD2 mutation status. In exome-wide analyses, African genetic ancestry was significantly associated with higher odds of mutation in KNCN and TMEM184B. Native American genetic ancestry was associated with a lower frequency of microsatellite instability-high tumors. The SBS11 mutational signature was associated with Native American genetic ancestry as well as Latino ethnicity. In an independent replication dataset, MSK-IMPACT, estimates of association were largely consistent in direction but nonsignificant. A meta-analysis of LC3 and MSK-IMPACT showed that African genetic ancestry was significantly associated with KRAS mutation status and MSI status. This work facilitates precision medicine initiatives by providing insights into the contribution of genetic ancestry to molecular features of colorectal tumors. Significance: Analysis of tumors from various populations can broadly characterize genomic landscapes and enhance precision medicine strategies.

Battlegrounds of treatment resistance: decoding the tumor microenvironment

The tumor microenvironment (TME) emerges as a formidable actor in the cancer treatment landscape, wielding the power to thwart therapeutic efficacy across various modalities, including chemotherapy, radiotherapy, immunotherapy, targeted therapy, and hormonal therapy. This intricate ecosystem comprising diverse cellular constituents, signaling molecules, and the extracellular matrix fosters a dynamic interplay that profoundly influences tumor behavior and treatment outcomes. This review explores the mechanisms through which the TME drives resistance to standard therapies, emphasizing key factors such as hypoxia, immune evasion, and metabolic reprogramming. Furthermore, we illuminate innovative strategies aimed at reprogramming this hostile environment, including the application of therapeutic vaccines, CAR T cell therapy, and combination immunotherapies designed to enhance anti-tumor responses. By advocating for multidimensional approaches that dismantle the TME's barriers to effective treatment, this review calls for a transformative shift in cancer treatment paradigms. By bridging the gap between the TME's complexities and targeted therapeutic strategies, we pave the way for targeted interventions that promise to enhance clinical outcomes and improve patient prognosis in the relentless battle against cancer.

Identifying distinct prognostic and predictive contributions of tumor epithelium versus tumor microenvironment in colorectal cancer

BACKGROUND

Accumulating evidence has suggested that cancer progression and therapeutic response depend on both tumor epithelium (EPI) and tumor microenvironment (TME). However, the dependency of clinical outcomes on the tumor EPI vs. the TME has neither been clearly defined nor quantified.

METHODS

We classified 2373 colorectal cancer (CRC) tumors into the consensus molecular subtypes (CMS1-4) and generated the 10-gene TMES and the 10-gene EPIS signatures as the serendipitous derivatives of the most (positively vs. negatively) correlated genes of a highly-prognostic, ~ 500-gene signature we previously identified. Distinct TME vs. EPI cellular features of the signature genes were identified by CIBERSORT deconvolution and validated by scRNASEQ in an independent public dataset.

RESULTS

The TMES signature was strongly associated with the immune/stromal TME-rich CMS1/CMS4 subtypes that portended worse survival, whereas the EPIS signature was predominantly related to the TME-poor, epithelial CMS2/CMS3 classes that portended better survival. Multivariable Cox regression analysis against 29 TME-related signatures revealed that the TMES signature was the most strikingly impacted by the "Cancer-associated fibroblasts" signature (HR: 10.87 vs. 0.13, both P < 0.0001). Moreover, the TMES score was strongly correlated with EMT, SRC activation and MEK inhibitor resistance in 2373 CRC tumors (Spearman r = 0.727, 0.802, 0.824, respectively), which was validated in two independent CRC datasets (n = 626 and n = 566). By contrast, the EPIS score was the dominant force in associating with longer progression free survival in cetuximab-treated metastatic CRC patients derived from two independent clinical trials (Logrank trend P = 0.0005/n = 80; P = 0.0013/n = 44). This finding was further validated in a large real-world clinico-genomics dataset with EGFR inhibitor therapy, which demonstrated that higher EPIS scores were associated with increased overall survival (EGFRi, Logrank trend P < 0.0001/n = 2343) and time on treatment (cetuximab, P = 0.003/n = 953; panitumumab, P < 0.0001/n = 1307).

CONCLUSIONS

Here we identified a pair of new, distinct 10-gene signatures (the EPIS vs. the TMES) capable of distinguishing the cellular contribution of the tumor EPI vs. the TME in determining CRC prognosis and therapeutic outcomes. With targeted approaches emerging to address both tumor epithelial cells and the TME, the EPIS vs. TMES signature scores may have a novel biomarker role to permit optimization of CRC therapy by identifying sensitive vs. resistant subpopulations.

Molecular Pathway and Immune Profile Analysis of IPMN-Derived Versus PanIN-Derived Pancreatic Ductal Adenocarcinomas

Intraductal papillary mucinous neoplasms (IPMN) are commonly detected pancreatic cysts that may transform into pancreatic ductal adenocarcinoma (PDAC). Predicting which IPMNs will progress to PDAC remains a clinical challenge. Moreover, identifying those clinically evident IPMNs for which a surveillance approach is best is a dire clinical need. Therefore, we aimed to identify molecular signatures that distinguished between PDAC with and without clinical evidence of an IPMN to identify novel molecular pathways related to IPMN-derived PDAC that could help guide biomarker development. Data from the Oncology Research Information Exchange Network (ORIEN) multi-institute sequencing project were utilized to analyze 66 PDAC cases from Moffitt Cancer Center and The Ohio State University Wexner Medical Center, for which tumor whole transcriptome sequencing datasets were generated. Cases were classified based on whether a tumor had originated from an IPMN (n = 16) or presumably through the pancreatic intraepithelial neoplasia (PanIN) pathway (n = 50). We then performed differential expression and pathway analysis using Gene-Set Enrichment Analysis (GSEA) and Pathway Analysis with Down-weighted Genes (PADOG) algorithms. We also analyzed immune profiles using the Tumor-Immune Microenvironment Deconvolution web portal for Bulk Transcriptomics (TIMEx). Both GSEA and TIMEx indicate that PanIN-derived PDAC tumors enrich inflammatory pathways (complement, hedgehog signaling, coagulation, inflammatory response, apical surface, IL-2/STAT5, IL-6/STAT3, EMT, KRAS signaling, apical junction, IFN-gamma, allograft rejection) and are comparatively richer in almost all immune cell types than those from IPMN-derived PDAC. IPMN-derived tumors were enriched for metabolic and energy-generating pathways (oxidative phosphorylation, unfolded protein response, pancreas beta cells, adipogenesis, fatty acid metabolism, protein secretion), and the most significantly upregulated genes (padj < 0.001) included mucin 2 (MUC2) and gastrokine-2 (GKN2). Further, the metabolic-linked gene signature enriched in the IPMN-derived samples is associated with a cluster of early-stage and long-survival (top 4th quartile) PDAC cases from The Cancer Genome Atlas (TCGA) expression database. Our data suggest that IPMN-derived and PanIN-derived PDACs differ in the expression of immune profiles and metabolic pathways. These initial findings warrant validation and follow-up to develop biomarker-based strategies for early PDAC detection and treatment.

Differential Infiltration of Key Immune T-Cell Populations Across Malignancies Varying by Immunogenic Potential and the Likelihood of Response to Immunotherapy

Background: Solid tumors vary by the immunogenic potential of the tumor microenvironment (TME) and the likelihood of response to immunotherapy. The emerging literature has identified key immune cell populations that significantly impact immune activation or suppression within the TME. This study investigated candidate T-cell populations and their differential infiltration within different tumor types as estimated from mRNA co-expression levels of the corresponding cellular markers. Methods: We analyzed the mRNA co-expression levels of cellular biomarkers that define stem-like tumor-infiltrating lymphocytes (TILs), tissue-resident memory T-cells (TRM), early dysfunctional T-cells, late dysfunctional T-cells, activated-potentially anti-tumor (APA) T-cells and Butyrophilin 3A (BTN3A) isoforms, utilizing clinical and transcriptomic data from 1892 patients diagnosed with melanoma, bladder, ovarian, or pancreatic carcinomas. Real-world data were collected under the Total Cancer Care Protocol and the Avatar® project (NCT03977402) across 18 cancer centers. Furthermore, we compared the survival outcomes following immune checkpoint inhibitors (ICIs) based on immune cell gene expression. Results: In melanoma and bladder cancer, the estimated infiltration of APA T-cells differed significantly (p = 4.67 × 10-12 and p = 5.80 × 10-12, respectively) compared to ovarian and pancreatic cancers. Ovarian cancer had lower TRM T-cell infiltration than melanoma, bladder, and pancreatic (p = 2.23 × 10-8, 3.86 × 10-28, and 7.85 × 10-9, respectively). Similar trends were noted with stem-like, early, and late dysfunctional T-cells. Melanoma and ovarian expressed BTN3A isoforms more than other malignancies. Higher densities of stem-like TILs; TRM, early and late dysfunctional T-cells; APA T-cells; and BTN3A isoforms were associated with increased survival in melanoma (p = 0.0075, 0.00059, 0.013, 0.005, 0.0016, and 0.041, respectively). The TRM gene signature was a moderate predictor of survival in the melanoma cohort (AUROC = 0.65), with similar findings in testing independent public datasets of ICI-treated patients with melanoma (AUROC 0.61-0.64). Conclusions: Key cellular elements related to immune activation are more heavily infiltrated within ICI-responsive versus non-responsive malignancies, supporting a central role in anti-tumor immunity. In melanoma patients treated with ICIs, higher densities of stem-like TILs, TRM T-cells, early dysfunctional T-cells, late dysfunctional T-cells, APA T-cells, and BTN3A isoforms were associated with improved survival.

Clonal Hematopoiesis in Patients With Human Immunodeficiency Virus and Cancer

BACKGROUND

Cancer-related deaths for people with human immunodeficiency virus (PWH) are increasing due to longer life expectancies and disparately poor cancer-related outcomes. We hypothesize that advanced biological aging contributes to cancer-related morbidity and mortality for PWH and cancer. We sought to determine the impact of clonal hematopoiesis (CH) on cancer disparities in PWH.

METHODS

We conducted a retrospective study to compare the prevalence and clinical outcomes of CH in PWH and people without HIV (PWoH) and cancer. Included in the study were PWH and similar PWoH based on tumor site, age, tumor sequence, and cancer treatment status. Biological aging was also measured using epigenetic methylation clocks.

RESULTS

In 136 patients with cancer, PWH had twice the prevalence of CH compared to similar PWoH (23% vs 11%, P = .07). After adjusting for patient characteristics, PWH were 4 times more likely than PWoH to have CH (odds ratio, 4.1 [95% confidence interval, 1.3-13.9]; P = .02). The effect of CH on survival was most pronounced in PWH, who had a 5-year survival rate of 38% if they had CH (vs 59% if no CH), compared to PWoH who had a 5-year survival rate of 75% if they had CH (vs 83% if no CH).

CONCLUSIONS

This study provides the first evidence that PWH may have a higher prevalence of CH than PWoH with the same cancers. CH may be an independent biological aging risk factor contributing to inferior survival for PWH and cancer.

Multicellular immune ecotypes within solid tumors predict real-world therapeutic benefits with immune checkpoint inhibitors

Background

Cancer initiation, progression, and immune evasion depend on the tumor microenvironment (TME). Thus, understanding the TME immune architecture is essential for understanding tumor metastasis and therapy response. This study aimed to create an immune cell states (CSs) atlas using bulk RNA-seq data enriched by eco-type analyses to resolve the complex immune architectures in the TME.

Methods

We employed EcoTyper, a machine-learning (ML) framework, to study the real-world prognostic significance of immune CSs and multicellular ecosystems, utilizing molecular data from 1,610 patients with multiple malignancies who underwent immune checkpoint inhibitor (ICI) therapy within the ORIEN Avatar cohort, a well-annotated real-world dataset.

Results

Our analysis revealed consistent ICI-specific prognostic TME carcinoma ecotypes (CEs) (including CE1, CE9, CE10) across our pan-cancer dataset, where CE1 being more lymphocyte-deficient and CE10 being more proinflammatory. Also, the analysis of specific immune CSs across different cancers showed consistent CD8+ and CD4+ T cell CS distribution patterns. Furthermore, survival analysis of the ORIEN ICI cohort demonstrated that ecotype CE9 is associated with the most favorable survival outcomes, while CE2 is linked to the least favorable outcomes. Notably, the melanoma-specific prognostic EcoTyper model confirmed that lower predicted risk scores are associated with improved survival and better response to immunotherapy. Finally, de novo discovery of ecotypes in the ORIEN ICI dataset identified Ecotype E3 as significantly associated with poorer survival outcomes.

Conclusion

Our findings offer important insights into refining the patient selection process for immunotherapy in real-world practice and guiding the creation of novel therapeutic strategies to target specific ecotypes within the TME.

Differences in Co-Expression of T Cell Co-Inhibitory and Co-Stimulatory Molecules with PD-1 Across Different Human Cancers

Purpose

The promise of immune checkpoint inhibitor (ICI) therapy underlines the importance of comprehensively investigating the rationale for combinations with diverse immune modulators across different cancer types. Given the progress made with PD1 blockade to date, we examined mRNA co-expression levels of PD-1 with 13 immune checkpoints, including co-inhibitory receptors (LAG3, CTLA4, PD-L1, TIGIT, TIM3, VISTA, BTLA) and co-stimulatory molecules (CD28, OX40, GITR, CD137, CD27, HVEM), using RNA-Seq by Expectation-Maximization (RSEM).

Methods

We analyzed real-world clinical and transcriptomic data from the Total Cancer Care Protocol (NCT03977402) and Avatar® project of patients with cancer treated within the Oncology Research Information Exchange Network (ORIEN) network. Using anti-PD1 as a backbone, we intended to investigate the rationale for combinations in different cancers. Pearson's R coefficients and associated P-values were calculated using SciPy 1.7.0.

Results

The co-expression of PD1 with 13 immune checkpoints and PD-L1 varies across selected malignancies included. In cutaneous melanoma, PD1 expression correlated significantly with four co-inhibitory receptors (LAG3, TIM3, TIGIT, VISTA) and one co-stimulatory molecule (CD137). In urothelial carcinoma, PD1 expression significantly correlated with four co-inhibitory (TIGIT, CTLA4, LAG3, VISTA) and four co-stimulatory (OX40, CD27, CD137, HVEM) molecules. In pancreatic adenocarcinoma, only CD28 showed a significant correlation with PD1 expression. No significant correlations with PD1 expression were found in the ovarian cancer cohort. Notably, melanoma and urothelial carcinoma exhibited a dominant co-expression of co-inhibitory molecules with PD1, indicative of exhausted T cells, in contrast to the co-stimulatory molecule dominance in ovarian and pancreatic cancers, suggesting less differentiated T cells.

Conclusions

Our findings highlight the potential for diverse combination strategies in immunotherapy, particularly with PD1 blockade, across various cancers.

Spectrum of somatic mutational features of colorectal tumors in ancestrally diverse populations

Ancestrally diverse and admixed populations, including the Hispanic/Latino/a/x/e community, are underrepresented in cancer genetic and genomic studies. Leveraging the Latino Colorectal Cancer Consortium, we analyzed whole exome sequencing data on tumor/normal pairs from 718 individuals with colorectal cancer (128 Latino, 469 non-Latino) to map somatic mutational features by ethnicity and genetic ancestry. Global proportions of African, East Asian, European, and Native American ancestries were estimated using ADMIXTURE. Associations between global genetic ancestry and somatic mutational features across genes were examined using logistic regression. TP53 , APC , and KRAS were the most recurrently mutated genes. Compared to non-Latino individuals, tumors from Latino individuals had fewer KRAS (OR=0.64, 95%CI=0.41-0.97, p=0.037) and PIK3CA mutations (OR=0.55, 95%CI=0.31-0.98, p=0.043). Genetic ancestry was associated with presence of somatic mutations in 39 genes (FDR-adjusted LRT p<0.05). Among these genes, a 10% increase in African ancestry was associated with significantly higher odds of mutation in KNCN (OR=1.34, 95%CI=1.09-1.66, p=5.74×10 -3 ) and TMEM184B (OR=1.53, 95%CI=1.10-2.12, p=0.011). Among RMGs, we found evidence of association between genetic ancestry and mutation status in CDC27 (LRT p=0.0084) and between SMAD2 mutation status and AFR ancestry (OR=1.14, 95%CI=1.00-1.30, p=0.046). Ancestry was not associated with tumor mutational burden. Individuals with above-average Native American ancestry had a lower frequency of microsatellite instable (MSI-H) vs microsatellite stable tumors (OR=0.45, 95%CI=0.21-0.99, p=0.048). Our findings provide new knowledge about the relationship between ancestral haplotypes and somatic mutational profiles that may be useful in developing precision medicine approaches and provide additional insight into genomic contributions to cancer disparities.

Significance

Our data in ancestrally diverse populations adds essential information to characterize mutational features in the colorectal cancer genome. These results will help enhance equity in the development of precision medicine strategies.

Feasibility and Clinical Utility of Reporting Hereditary Cancer Predisposition Pathogenic Variants Identified in Research Germline Sequencing: A Prospective Interventional Study

PURPOSE

Patients with cancer frequently undergo research-grade germline sequencing but clinically actionable results are not routinely disclosed. The objective of this study is to evaluate the feasibility of reporting clinically relevant secondary findings (SF) identified in germline research sequencing using the institutional molecular tumor board (MTB) and the treating oncology physician.

METHODS

This prospective, interventional cohort study enrolled Total Cancer Care participants with any cancer diagnosis at a single institution. Patients underwent research-grade germline whole-exome sequencing, with bioinformatic analysis in a Clinical Laboratory Improvement Amendments-certified laboratory to verify pathogenic/likely pathogenic germline variants (PGVs) in any American College of Medical Genomics and Genetics SF v2.0 genes. After a protocol modification in consenting patients, the MTB reported PGVs to treating oncology physicians with recommendations for referral to a licensed genetic counselor and clinical confirmatory testing.

RESULTS

Of the 781 enrolled participants, 32 (4.1%) harbored cancer predisposition PGVs, 24 (3.1%) were heterozygous carriers of an autosomal recessive cancer predisposition syndrome, and 14 (1.8%) had other hereditary disease PGVs. Guideline-directed testing would have missed 37.5% (12/32) of the inherited cancer predisposition PGVs, which included BRCA1, BRCA2, MSH6, SDHAF2, SDHB, and TP53 variants. Three hundred fifteen participants consented to reporting results; results for all living patients were reported to the clinical team with half referred to a licensed genetic counselor. There was concordance between all research variants identified in patients (n = 9) who underwent clinical confirmatory sequencing.

CONCLUSION

MTB reporting of research-grade germline sequencing to the clinical oncology team is feasible. Over a third of PGVs identified using a universal testing strategy would have been missed by guideline-based approach, suggesting a role for expanding germline testing.

Pathways to lung cancer diagnosis among individuals who did not receive lung cancer screening: a qualitative study

BACKGROUND

Although early detection of lung cancer through screening is associated with better prognosis, most lung cancers are diagnosed among unscreened individuals. We therefore sought to characterize pathways to lung cancer diagnosis among unscreened individuals.

METHODS

Participants were individuals with lung cancer who did not undergo asymptomatic lung cancer screening (n = 13) and healthcare providers who may be involved in the pathway to lung cancer diagnosis (n = 13). We conducted semi-structured interviews to identify themes in lung cancer patients' narratives of their cancer diagnoses and providers' personal and/or professional experiences of various pathways to lung cancer diagnoses, to identify delays in diagnosis. We audio-recorded, transcribed, and coded interviews in two stages. First, we conducted deductive coding using three time-period intervals from the Models of Pathways to Treatment framework: appraisal, help-seeking, and diagnostic (i.e., excluding pre-treatment). Second, we conducted inductive coding to identify themes within each time-period interval, and classified these themes as either barriers or facilitators to diagnosis. Coding and thematic summarization were completed independently by two separate analysts who discussed for consensus.

RESULTS

Eight of the patient participants had formerly smoked, and five had never smoked. We identified eight barrier/facilitator themes within the three time-period intervals. Within the appraisal interval, the barrier theme was (1) minimization or misattribution of symptoms, and the facilitator theme was (2) acknowledgment of symptoms. Within the help-seeking interval, the barrier theme was (3) hesitancy to seek care, and the facilitator theme was (4) routine care. Within the diagnosis interval, barrier themes were (5) health system challenges, and (6) social determinants of health; and facilitator themes were (7) severe symptoms and known risk factors, and (8) self-advocacy. Many themes were interrelated, including minimization or misattribution of symptoms and hesitancy to seek care, which may collectively contribute to care and imaging delays.

CONCLUSIONS

Interventions to reduce hesitancy to seek care may facilitate timely lung cancer diagnoses. More prompt referral to imaging-especially computed tomography (CT)-among symptomatic patients, along with patient self-advocacy for imaging, may reduce delays in diagnosis.

Clonal Hematopoiesis as a Molecular Risk Factor for Doxorubicin-Induced Cardiotoxicity: A Proof-of-Concept Study

PURPOSE

The main dose-limiting toxicity of anthracyclines is cardiotoxicity. Clonal hematopoiesis (CH), somatic mutations in hematopoietic stem or progenitor cells in patients without hematologic malignancy, is also associated with risk for adverse cardiovascular events and worse outcomes overall. We hypothesize that CH increases risk for doxorubicin-induced cardiotoxicity (DIC).

METHODS

We conducted a retrospective cohort study in patients treated with doxorubicin for cancer (N = 100). Patients (n = 25) had incident symptomatic heart failure, decline in left ventricular ejection fraction, or arrhythmia. CH was identified using paired peripheral blood and tumor DNA.

RESULTS

After adjusting for age at doxorubicin initiation, diabetes, dyslipidemia, and chest radiation, high cumulative dose of doxorubicin (>240 mg/m2; odds ratio [OR], 7.00; 95% CI, 1.77 to 27.74; P = .0056), CH (OR, 8.58; 95% CI, 2.05 to 35.99; P = .0033), and history of smoking (OR, 3.15; 95% CI, 1.00 to 9.93; P = .0495) were associated with DIC.

CONCLUSION

This study provides preliminary evidence for CH as a predictive risk factor for DIC, which, with further investigation, could serve as an important precision medicine biomarker for the large number of patients with cancer who have CH.

Whole-Exome sequencing analysis identified TMSB10/TRABD2A locus to be associated with carfilzomib-related cardiotoxicity among patients with multiple myeloma

Background

Proteasome inhibitor Carfilzomib (CFZ) is effective in treating patients with refractory or relapsed multiple myeloma (MM) but has been associated with cardiovascular adverse events (CVAE) such as hypertension, cardiomyopathy, and heart failure. This study aimed to investigate the contribution of germline genetic variants in protein-coding genes in CFZ-CVAE among MM patients using whole-exome sequencing (WES) analysis.

Methods

Exome-wide single-variant association analysis, gene-based analysis, and rare variant analyses were performed on 603,920 variants in 247 patients with MM who have been treated with CFZ and enrolled in the Oncology Research Information Exchange Network (ORIEN) at the Moffitt Cancer Center. Separate analyses were performed in European Americans and African Americans followed by a trans-ethnic meta-analysis.

Results

The most significant variant in the exome-wide single variant analysis was a missense variant rs7148 in the thymosin beta-10/TraB Domain Containing 2A (TMSB10/TRABD2A) locus. The effect allele of rs7148 was associated with a higher risk of CVAE [odds ratio (OR) = 9.3 with a 95% confidence interval of 3.9-22.3, p = 5.42*10^-7]. MM patients with rs7148 AG or AA genotype had a higher risk of CVAE (50%) than those with GG genotype (10%). rs7148 is an expression quantitative trait locus (eQTL) for TRABD2A and TMSB10. The gene-based analysis also showed TRABD2A as the most significant gene associated with CFZ-CVAE (p = 1.06*10^-6).

Conclusions

We identified a missense SNP rs7148 in the TMSB10/TRABD2A as associated with CFZ-CVAE in MM patients. More investigation is needed to understand the underlying mechanisms of these associations.

Exploiting convergent phenotypes to derive a pan-cancer cisplatin response gene expression signature

Precision medicine offers remarkable potential for the treatment of cancer, but is largely focused on tumors that harbor actionable mutations. Gene expression signatures can expand the scope of precision medicine by predicting response to traditional (cytotoxic) chemotherapy agents without relying on changes in mutational status. We present a new signature extraction method, inspired by the principle of convergent phenotypes, which states that tumors with disparate genetic backgrounds may evolve similar phenotypes independently. This evolutionary-informed method can be utilized to produce consensus signatures predictive of response to over 200 chemotherapeutic drugs found in the Genomics of Drug Sensitivity in Cancer (GDSC) Database. Here, we demonstrate its use by extracting the Cisplatin Response Signature (CisSig). We show that this signature can predict cisplatin response within carcinoma-based cell lines from the GDSC database, and expression of the signatures aligns with clinical trends seen in independent datasets of tumor samples from The Cancer Genome Atlas (TCGA) and Total Cancer Care (TCC) database. Finally, we demonstrate preliminary validation of CisSig for use in muscle-invasive bladder cancer, predicting overall survival in a small cohort of patients who undergo cisplatin-containing chemotherapy. This methodology can be used to produce robust signatures that, with further clinical validation, may be used for the prediction of traditional chemotherapeutic response, dramatically increasing the reach of personalized medicine in cancer.

Validation of PRKCB Immunohistochemistry as a Biomarker for the Diagnosis of Ewing Sarcoma

Background: Ewing sarcoma (ES) can be confirmed by identifying the EWSR1-FLI1 fusion transcript. This study is to investigate whether immunostaining (IHC) of PRKCB-a protein directly regulated by EWSR1-FLI1 is a surrogate maker for diagnosing ES in routine practice. Methods: Microarray gene expression analyses were conducted. RKCB IHC was applied to 69 ES confirmed by morphology and molecular methods, and 41 non-Ewing small round cell tumors. EWSR1 rearrangement, EWSR1-FLI1 fusion or t(11;22)(q24;q12) were identified by fluorescence in situ hybridization, reverse transcriptase polymerase chain reaction, or cytogenetic analysis, respectively. Results: Gene array analyses showed significant overexpression of the PRKCB in ES. PRKCB IHC was positive in 19 cases of ES with EWSR1-FLI1 fusion, 3 cases with cytogenetic 11:22 translocation and 59 cases with EWSR1 rearrangement while negative in only one EWSR1 rearranged case. PRKCB IHC is sensitive (98%) and specific (96%) in detecting EWSR1 rearranged ES. Conclusions: PRKCB is a reliable antibody for diagnosing ES in routine practice.

Oxidized Mitochondrial DNA Engages TLR9 to Activate the NLRP3 Inflammasome in Myelodysplastic Syndromes

Myelodysplastic Syndromes (MDSs) are bone marrow (BM) failure malignancies characterized by constitutive innate immune activation, including NLRP3 inflammasome driven pyroptotic cell death. We recently reported that the danger-associated molecular pattern (DAMP) oxidized mitochondrial DNA (ox-mtDNA) is diagnostically increased in MDS plasma although the functional consequences remain poorly defined. We hypothesized that ox-mtDNA is released into the cytosol, upon NLRP3 inflammasome pyroptotic lysis, where it propagates and further enhances the inflammatory cell death feed-forward loop onto healthy tissues. This activation can be mediated via ox-mtDNA engagement of Toll-like receptor 9 (TLR9), an endosomal DNA sensing pattern recognition receptor known to prime and activate the inflammasome propagating the IFN-induced inflammatory response in neighboring healthy hematopoietic stem and progenitor cells (HSPCs), which presents a potentially targetable axis for the reduction in inflammasome activation in MDS. We found that extracellular ox-mtDNA activates the TLR9-MyD88-inflammasome pathway, demonstrated by increased lysosome formation, IRF7 translocation, and interferon-stimulated gene (ISG) production. Extracellular ox-mtDNA also induces TLR9 redistribution in MDS HSPCs to the cell surface. The effects on NLRP3 inflammasome activation were validated by blocking TLR9 activation via chemical inhibition and CRISPR knockout, demonstrating that TLR9 was necessary for ox-mtDNA-mediated inflammasome activation. Conversely, lentiviral overexpression of TLR9 sensitized cells to ox-mtDNA. Lastly, inhibiting TLR9 restored hematopoietic colony formation in MDS BM. We conclude that MDS HSPCs are primed for inflammasome activation via ox-mtDNA released by pyroptotic cells. Blocking the TLR9/ox-mtDNA axis may prove to be a novel therapeutic strategy for MDS.

Psychosocial characteristics of patients undergoing cellular immunotherapies and their caregivers across time

Chimeric antigen receptor T-cells and other immunotherapies have markedly changed the paradigm of treatment for patients with relapsed or refractory hematologic malignancies. While notable in efficacy, immunotherapy is characterized by a significant possibility of life-threatening side effects. Consequently, patients are often required to have informal family caregivers present and to stay near the treating center for several weeks after cell infusion. Further, the responsibility of managing a great deal of physical care and emotional support falls to these caregivers. Given the novelty of immunotherapy treatment, there is a need to better understand the psychosocial experience of patients receiving this treatment and their caregivers. This article describes the psychosocial characteristics of patients undergoing cellular immunotherapies and their caregivers across time, including patient/caregiver distress, coping, and caregiver burden and preparedness.

Loss of the endocytic tumor suppressor HD-PTP phenocopies LKB1 and promotes RAS-driven oncogenesis

Oncogenic RAS mutations drive aggressive cancers that are difficult to treat in the clinic, and while direct inhibition of the most common KRAS variant in lung adenocarcinoma (G12C) is undergoing clinical evaluation, a wide spectrum of oncogenic RAS variants together make up a large percentage of untargetable lung and GI cancers. Here we report that loss-of-function alterations (mutations and deep deletions) in the gene that encodes HD-PTP (PTPN23) occur in up to 14% of lung cancers in the ORIEN Avatar lung cancer cohort, associate with adenosquamous histology, and occur alongside an altered spectrum of KRAS alleles. Furthermore, we show that in publicly available early-stage NSCLC studies loss of HD-PTP is mutually exclusive with loss of LKB1, which suggests they restrict a common oncogenic pathway in early lung tumorigenesis. In support of this, knockdown of HD-PTP in RAS-transformed lung cancer cells is sufficient to promote FAK-dependent invasion. Lastly, knockdown of the Drosophila homolog of HD-PTP (dHD-PTP/Myopic) synergizes to promote RAS-dependent neoplastic progression. Our findings highlight a novel tumor suppressor that can restrict RAS-driven lung cancer oncogenesis and identify a targetable pathway for personalized therapeutic approaches for adenosquamous lung cancer.

Biomarkers of radioresistance in head and neck squamous cell carcinomas

PURPOSE

Head and neck squamous cell carcinoma (HNSCC) is a major cause of morbidity and mortality. Although HNSCC is mainly caused by tobacco and alcohol consumption, infection by Human Papilloma Virus (HPV) has been also associated with the increasing incidence of oropharyngeal squamous cell carcinomas (OPSCC) during the past decades. HPV-positive HNSCC is characterized by a higher radiosensitivity compared to HPV-negative tumor. While several clinical trials are evaluating de-escaladed radiation doses strategies in HPV-positive HNSCC, molecular mechanisms associated with relative radioresistance in HPV-negative HNSCC are still broadly unknown. Our goal was to review recently proposed biomarkers of radioresistance in this setting, which may be useful for stratifying tumor's patient according to predicted level of radioresistance.

CONCLUSIONS

most of biomarkers of radioresistance in HPV-negative HNSCC are identified using a hypothesis-driven approach, based on molecular mechanisms known to play a key role during carcinogenesis, compared to an unsupervised data-driven approach regardless the biological rational. DNA repair and hypoxia are the two most widely investigated biological and targetable pathways related to radioresistance in HNSCC. The better understanding of molecular mechanisms and biomarkers of radioresistance in HPV-negative HNSCC could help for the development of radiosensitization strategies, based on targetable biomarkers, in radioresistant tumors as well as de-escalation radiation dose strategies, based on biological level of radioresistance, in radiosensitive tumors.

A pilot study to evaluate tissue- and plasma-based DNA driver mutations in a cohort of patients with pancreatic intraductal papillary mucinous neoplasms

Intraductal papillary mucinous neoplasms (IPMNs) are precursor lesions to pancreatic ductal adenocarcinoma that are challenging to manage due to limited imaging, cytologic, and molecular markers that accurately classify lesions, grade of dysplasia, or focus of invasion preoperatively. The objective of this pilot study was to determine the frequency and type of DNA mutations in a cohort of surgically resected, pathologically confirmed IPMN, and to determine if concordant mutations are detectable in paired pretreatment plasma samples. Formalin-fixed paraffin-embedded (FFPE) tissue from 46 surgically resected IPMNs (31 low-grade, 15 high-grade) and paired plasma from a subset of 15 IPMN cases (10 low-grade, 5 high-grade) were subjected to targeted mutation analysis using a QIAseq Targeted DNA Custom Panel. Common driver mutations were detected in FFPE from 44 of 46 (95.6%) IPMN cases spanning all grades; the most common DNA mutations included: KRAS (80%), RNF43 (24%), and GNAS (43%). Of note, we observed a significant increase in the frequency of RNF43 mutations from low-grade to high-grade IPMNs associated or concomitant with invasive carcinoma (trend test, P = 0.01). Among the subset of cases with paired plasma, driver mutations identified in the IPMNs were not detected in circulation. Overall, our results indicate that mutational burden for IPMNs is a common occurrence, even in low-grade IPMNs. Furthermore, although blood-based biopsies are an attractive, noninvasive method for detecting somatic DNA mutations, the QIAseq panel was not sensitive enough to detect driver mutations that existed in IPMN tissue using paired plasma in the volume we were able to retrieve for this retrospective study.

Surface modification of carbon nitride dots by nanoarchitectonics for better drug loading and higher cancer selectivity

Carbon Dots (CDs) have recently attracted a considerable amount of attention thanks to their well-documented biocompatibility, tunable photoluminescence, and excellent water solubility. However, CDs need further analysis before their potential use in clinical trials. Previously, we reported a new type of carbon nitride dot (CND) that displayed selective cancer uptake traits attributed to structural resemblances between CNDs and glutamine. Here, the effects of surface structural differences on the cellular uptake of CNDs are further investigated to understand their selective cancer cell uptake trend. Beyond enhanced drug loading on modified CNDs, our cytotoxicity, western blotting and bioimaging studies proposed that modified CNDs' cellular uptake mechanism is thoroughly linked with ASCT2 and LAT1 transporters. Therefore, CNDs have a promising trait of selective cancer cell targeting by utilizing highly expressed transporters on cancer cells. Additionally, drug loaded CNDs exhibited improved anti-cancer efficacies towards cancer cells along with good non-tumor biocompatibilities.

Data-Driven Identification of Biomarkers for In Situ Monitoring of Drug Treatment in Bladder Cancer Organoids

Three-dimensional (3D) organoid culture recapitulating patient-specific histopathological and molecular diversity offers great promise for precision medicine in cancer. In this study, we established label-free imaging procedures, including Raman microspectroscopy (RMS) and fluorescence lifetime imaging microscopy (FLIM), for in situ cellular analysis and metabolic monitoring of drug treatment efficacy. Primary tumor and urine specimens were utilized to generate bladder cancer organoids, which were further treated with various concentrations of pharmaceutical agents relevant for the treatment of bladder cancer (i.e., cisplatin, venetoclax). Direct cellular response upon drug treatment was monitored by RMS. Raman spectra of treated and untreated bladder cancer organoids were compared using multivariate data analysis to monitor the impact of drugs on subcellular structures such as nuclei and mitochondria based on shifts and intensity changes of specific molecular vibrations. The effects of different drugs on cell metabolism were assessed by the local autofluorophore environment of NADH and FAD, determined by multiexponential fitting of lifetime decays. Data-driven neural network and data validation analyses (k-means clustering) were performed to retrieve additional and non-biased biomarkers for the classification of drug-specific responsiveness. Together, FLIM and RMS allowed for non-invasive and molecular-sensitive monitoring of tumor-drug interactions, providing the potential to determine and optimize patient-specific treatment efficacy.

Racial and ethnic differences in clonal hematopoiesis, tumor markers, and outcomes of patients with multiple myeloma

Age of onset and survival disparities exist for racial and ethnic minority patients diagnosed with MM.

Differences in somatic mutations in tumor and blood (ie, clonal hematopoiesis) may contribute to disparities in outcomes observed.

Multiple myeloma (MM) incidence, mortality, and survival vary by race and ethnicity, but the causes of differences remain unclear. We investigated demographic, clinical, and molecular features of diverse MM patients to elucidate mechanisms driving clinical disparities. This study included 495 MM patients (self-reported Hispanic, n = 45; non-Hispanic Black, n = 52; non-Hispanic White, n = 398). Hispanic and non-Hispanic Black individuals had an earlier age of onset than non-Hispanic White individuals (53 and 57 vs 63 years, respectively, P < .001). There were no differences in treatment by race and ethnicity groups, but non-Hispanic Black patients had a longer time to hematopoietic cell transplant than non-Hispanic White patients (376 days vs 248 days; P = .01). Overall survival (OS) was improved for non-Hispanic Black compared with non-Hispanic White patients (HR, 0.50; 95% CI, 0.31-0.81; P = .005), although this association was attenuated after adjusting for clinical features (HR, 0.62; 95% CI, 0.37-1.03; P = .06). Tumor mutations in IRF4 were most common in Hispanic patients, and mutations in SP140, AUTS2, and SETD2 were most common in non-Hispanic Black patients. Differences in tumor expression of BCL7A, SPEF2, and ANKRD26 by race and ethnicity were observed. Clonal hematopoiesis was detected in 12% of patients and associated with inferior OS in non-Hispanic Black patients compared with patients without clonal hematopoiesis (HR, 4.36; 95% CI, 1.36-14.00). This study provides insight into differences in molecular features that may drive clinical disparities in MM patients receiving comparable treatment, with the novel inclusion of Hispanic individuals.

Transcriptomic Determinants of Response to Pembrolizumab Monotherapy across Solid Tumor Types

PURPOSE

To explore relationships between biological gene expression signatures and pembrolizumab response.

EXPERIMENTAL DESIGN

RNA-sequencing data on baseline tumor tissue from 1,188 patients across seven tumor types treated with pembrolizumab monotherapy in nine clinical trials were used. A total of 11 prespecified gene expression signatures [18-gene T-cell-inflamed gene expression profile (TcellinfGEP), angiogenesis, hypoxia, glycolysis, proliferation, MYC, RAS, granulocytic myeloid-derived suppressor cell (gMDSC), monocytic myeloid-derived suppressor cell (mMDSC), stroma/epithelial-to-mesenchymal transition (EMT)/TGFβ, and WNT] were evaluated for their relationship to objective response rate (per RECIST, version 1.1). Logistic regression analysis of response for consensus signatures was adjusted for tumor type, Eastern Cooperative Oncology Group performance status, and TcellinfGEP, an approach equivalent to evaluating the association between response and the residuals of consensus signatures after detrending them for their relationship with the TcellinfGEP (previously identified as a determinant of pembrolizumab response) and tumor type. Testing of the 10 prespecified non-TcellinfGEP consensus signatures for negative association [except proliferation (hypothesized positive association)] with response was adjusted for multiplicity.

RESULTS

Covariance patterns of the 11 signatures (including TcellinfGEP) identified in Merck-Moffitt and The Cancer Genome Atlas datasets showed highly concordant coexpression patterns in the RNA-sequencing data from pembrolizumab trials. TcellinfGEP was positively associated with response; signatures for angiogenesis, mMDSC, and stroma/EMT/TGFβ were negatively associated with response to pembrolizumab monotherapy.

CONCLUSIONS

These findings suggest that features beyond IFNγ-related T-cell inflammation may be relevant to anti-programmed death 1 monotherapy response and may define other axes of tumor biology as candidates for pembrolizumab combinations. See related commentary by Cho et al., p. 1479.

The Radiosensitivity Index (RSI) Gene Signature Identifies Distinct Tumor Immune Microenvironment Characteristics Associated with Susceptibility to Radiotherapy

PURPOSE

Radiotherapy (RT) is a mainstay of cancer care and accumulating evidence suggests the potential for synergism with components of the immune response. However, little data describes the tumor immune contexture in relation to RT-sensitivity. To address this challenge, we employed the radiation sensitivity index (RSI) gene signature to estimate the RT-sensitivity of >10,000 primary tumors and characterized their immune microenvironments in relation to the RSI.

MATERIAL AND METHODS

We analyzed gene expression profiles of 10,469 primary tumors (31 types) within a prospective tissue collection protocol. The RT-sensitivity of each tumor was estimated by the RSI and respective distributions were characterized. The tumor biology measured by the RSI was evaluated by differentially expressed genes (DEGs) combined with single sample gene set enrichment analysis (ssGSEA). Differences in the expression of immune regulatory molecules were assessed and deconvolution algorithms were used to estimate immune cell infiltrates in relation to the RSI. A subset (n=2,368) of tumors underwent DNA sequencing for mutational frequency characterization.

RESULTS

We identified a wide range of RSI values within and across various tumor types, with several demonstrating non-unimodal distributions (e.g. colon, renal, lung, prostate, esophagus, pancreas and PAM50 breast subtypes; p <0.05). Across all tumors types, stratifying RSI at a tumor type-specific median, identified 7,148 DEGs, of which 146 were coordinate in direction. Network topology analysis demonstrates RSI measures a coordinated STAT1, IRF1, and CCL4/MIP-1β transcriptional network. Tumors with an estimated high sensitivity to RT demonstrated distinct enrichment of interferon-associated signaling pathways and immune cell infiltrates (e.g. CD8+ T cells, activated natural killer cells, M1-macrophages; q < 0.05), which was in the context of diverse expression patterns of various immunoregulatory molecules.

CONCLUSION

This analysis describes the immune microenvironments of patient tumors in relation to the RSI gene expression signature.

An integrative gene expression signature analysis identifies CMS4 KRAS-mutated colorectal cancers sensitive to combined MEK and SRC targeted therapy

BACKGROUND

Over half of colorectal cancers (CRCs) are hard-wired to RAS/RAF/MEK/ERK pathway oncogenic signaling. However, the promise of targeted therapeutic inhibitors, has been tempered by disappointing clinical activity, likely due to complex resistance mechanisms that are not well understood. This study aims to investigate MEK inhibitor-associated resistance signaling and identify subpopulation(s) of CRC patients who may be sensitive to biomarker-driven drug combination(s).

METHODS

We classified 2250 primary and metastatic human CRC tumors by consensus molecular subtypes (CMS). For each tumor, we generated multiple gene expression signature scores measuring MEK pathway activation, MEKi "bypass" resistance, SRC activation, dasatinib sensitivity, EMT, PC1, Hu-Lgr5-ISC, Hu-EphB2-ISC, Hu-Late TA, Hu-Proliferation, and WNT activity. We carried out correlation, survival and other bioinformatic analyses. Validation analyses were performed in two independent publicly available CRC tumor datasets (n = 585 and n = 677) and a CRC cell line dataset (n = 154).

RESULTS

Here we report a central role of SRC in mediating "bypass"-resistance to MEK inhibition (MEKi), primarily in cancer stem cells (CSCs). Our integrated and comprehensive gene expression signature analyses in 2250 CRC tumors reveal that MEKi-resistance is strikingly-correlated with SRC activation (Spearman P < 10-320), which is similarly associated with EMT (epithelial to mesenchymal transition), regional metastasis and disease recurrence with poor prognosis. Deeper analysis shows that both MEKi-resistance and SRC activation are preferentially associated with a mesenchymal CSC phenotype. This association is validated in additional independent CRC tumor and cell lines datasets. The CMS classification analysis demonstrates the strikingly-distinct associations of CMS1-4 subtypes with the MEKi-resistance and SRC activation. Importantly, MEKi + SRCi sensitivities are predicted to occur predominantly in the KRAS mutant, mesenchymal CSC-like CMS4 CRCs.

CONCLUSIONS

Large human tumor gene expression datasets representing CRC heterogeneity can provide deep biological insights heretofore not possible with cell line models, suggesting novel repurposed drug combinations. We identified SRC as a common targetable node--an Achilles' heel--in MEKi-targeted therapy-associated resistance in mesenchymal stem-like CRCs, which may help development of a biomarker-driven drug combination (MEKi + SRCi) to treat problematic subpopulations of CRC.

Raman Imaging and Fluorescence Lifetime Imaging Microscopy for Diagnosis of Cancer State and Metabolic Monitoring

Hurdles for effective tumor therapy are delayed detection and limited effectiveness of systemic drug therapies by patient-specific multidrug resistance. Non-invasive bioimaging tools such as fluorescence lifetime imaging microscopy (FLIM) and Raman-microspectroscopy have evolved over the last decade, providing the potential to be translated into clinics for early-stage disease detection, in vitro drug screening, and drug efficacy studies in personalized medicine. Accessing tissue- and cell-specific spectral signatures, Raman microspectroscopy has emerged as a diagnostic tool to identify precancerous lesions, cancer stages, or cell malignancy. In vivo Raman measurements have been enabled by recent technological advances in Raman endoscopy and signal-enhancing setups such as coherent anti-stokes Raman spectroscopy or surface-enhanced Raman spectroscopy. FLIM enables in situ investigations of metabolic processes such as glycolysis, oxidative stress, or mitochondrial activity by using the autofluorescence of co-enzymes NADH and FAD, which are associated with intrinsic proteins as a direct measure of tumor metabolism, cell death stages and drug efficacy. The combination of non-invasive and molecular-sensitive in situ techniques and advanced 3D tumor models such as patient-derived organoids or microtumors allows the recapitulation of tumor physiology and metabolism in vitro and facilitates the screening for patient-individualized drug treatment options.

APC and TP53 Mutations Predict Cetuximab Sensitivity across Consensus Molecular Subtypes

Simple Summary

Colorectal cancer (CRC) is a major cause of cancer deaths. Cetuximab is an FDA-approved, underutilized therapeutic targeting the epidermal growth factor receptor (EGFR) in metastatic CRC. To date, despite selection of patients with wild-type RAS, it is still difficult to identify patients who may benefit from EGFR inhibitor (e.g., cetuximab) therapy. Our aim is to molecularly classify CRC patients to better identify subpopulations sensitive to EGFR targeted therapy. APC and TP53 are two major tumor suppressor genes in CRC whose mutations contribute to tumor initiation and progression and may identify cetuximab-sensitive tumors. Recently, it has been suggested that the consensus molecular subtype (CMS) classification may be used to help identify cetuximab-sensitive patients. Here, we report an analysis of multiple CRC tumor/PDX/cell line datasets using combined APC and TP53 mutations to refine the CMS classification to better predict responses to cetuximab to improve patient outcomes.

Abstract

Recently, it was suggested that consensus molecular subtyping (CMS) may aide in predicting response to EGFR inhibitor (cetuximab) therapies. We recently identified that APC and TP53 as two tumor suppressor genes, when mutated, may enhance cetuximab sensitivity and may represent easily measured biomarkers in tumors or blood. Our study aimed to use APC and TP53 mutations (AP) to refine the CMS classification to better predict responses to cetuximab. In total, 433 CRC tumors were classified into CMS1-4 subtypes. The cetuximab sensitivity (CTX-S) signature scores of AP vs. non-AP tumors were determined across each of the CMS classes. Tumors harboring combined AP mutations were predominantly enriched in the CMS2 class, and to a lesser degree, in the CMS4 class. On the other hand, AP mutated CRCs had significantly higher CTX-S scores compared to non-AP CRCs across all CMS classes. Similar results were also obtained in independent TCGA tumor collections (n = 531) and in PDMR PDX/PDO/PDC models (n = 477). In addition, the in vitro cetuximab growth inhibition was preferentially associated with the CMS2 cell lines harboring A/P genotypes. In conclusion, the AP mutation signature represents a convenient biomarker that refines the CMS classification to identify CRC subpopulations predicted to be sensitive to EGFR targeted therapies.

Tumor-immune ecosystem dynamics define an individual Radiation Immune Score to predict pan-cancer radiocurability

Radiotherapy efficacy is the result of radiation-mediated cytotoxicity coupled with stimulation of antitumor immune responses. We develop an in silico 3-dimensional agent-based model of diverse tumor-immune ecosystems (TIES) represented as anti- or pro-tumor immune phenotypes. We validate the model in 10,469 patients across 31 tumor types by demonstrating that clinically detected tumors have pro-tumor TIES. We then quantify the likelihood radiation induces antitumor TIES shifts toward immune-mediated tumor elimination by developing the individual Radiation Immune Score (iRIS). We show iRIS distribution across 31 tumor types is consistent with the clinical effectiveness of radiotherapy, and in combination with a molecular radiosensitivity index (RSI) combines to predict pan-cancer radiocurability. We show that iRIS correlates with local control and survival in a separate cohort of 59 lung cancer patients treated with radiation. In combination, iRIS and RSI predict radiation-induced TIES shifts in individual patients and identify candidates for radiation de-escalation and treatment escalation. This is the first clinically and biologically validated computational model to simulate and predict pan-cancer response and outcomes via the perturbation of the TIES by radiotherapy.

Real-World Evaluation of Universal Germline Screening for Cancer Treatment-Relevant Pharmacogenes

The purpose of this study was to determine the frequency of clinically actionable treatment-relevant germline pharmacogenomic variants in patients with cancer and assess the real-world clinical utility of universal screening using whole-exome sequencing in this population. Cancer patients underwent research-grade germline whole-exome sequencing as a component of sequencing for somatic variants. Analysis in a clinical bioinformatics pipeline identified clinically actionable pharmacogenomic variants. Clinical Pharmacogenetics Implementation Consortium guidelines defined clinical actionability. We assessed clinical utility by reviewing electronic health records to determine the frequency of patients receiving pharmacogenomically actionable anti-cancer agents and associated outcomes. This observational study evaluated 291 patients with cancer. More than 90% carried any clinically relevant pharmacogenetic variant. At least one disease-relevant variant impacting anti-cancer agents was identified in 26.5% (77/291). Nine patients with toxicity-associated pharmacogenomic variants were treated with a relevant medication: seven UGT1A1 intermediate metabolizers were treated with irinotecan, one intermediate DPYD metabolizer was treated with 5-fluorouracil, and one TPMT poor metabolizer was treated with mercaptopurine. These individuals were more likely to experience treatment-associated toxicities than their wild-type counterparts (p = 0.0567). One UGT1A1 heterozygote died after a single dose of irinotecan due to irinotecan-related adverse effects. Identifying germline pharmacogenomic variants was feasible using whole-exome sequencing. Actionable pharmacogenetic variants are common and relevant to patients undergoing cancer treatment. Universal pharmacogenomic screening can be performed using whole-exome sequencing data originally obtained for quality control purposes and could be considered for patients who are candidates for irinotecan, 5-fluorouracil, capecitabine, and mercaptopurine.

Enabling Precision Medicine in Cancer Care Through a Molecular Data Warehouse: The Moffitt Experience

PURPOSE

The use of genomics within cancer research and clinical oncology practice has become commonplace. Efforts such as The Cancer Genome Atlas have characterized the cancer genome and suggested a wealth of targets for implementing precision medicine strategies for patients with cancer. The data produced from research studies and clinical care have many potential secondary uses beyond their originally intended purpose. Effective storage, query, retrieval, and visualization of these data are essential to create an infrastructure to enable new discoveries in cancer research.

METHODS

Moffitt Cancer Center implemented a molecular data warehouse to complement the extensive enterprise clinical data warehouse (Health and Research Informatics). Seven different sequencing experiment types were included in the warehouse, with data from institutional research studies and clinical sequencing.

RESULTS

The implementation of the molecular warehouse involved the close collaboration of many teams with different expertise and a use case-focused approach. Cornerstones of project success included project planning, open communication, institutional buy-in, piloting the implementation, implementing custom solutions to address specific problems, data quality improvement, and data governance, unique aspects of which are featured here. We describe our experience in selecting, configuring, and loading molecular data into the molecular data warehouse. Specifically, we developed solutions for heterogeneous genomic sequencing cohorts (many different platforms) and integration with our existing clinical data warehouse.

CONCLUSION

The implementation was ultimately successful despite challenges encountered, many of which can be generalized to other research cancer centers.

Genomic identification of sarcoma radiosensitivity and the clinical implications for radiation dose personalization

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Soft tissue sarcomas have traditionally been treated with a one-size fits all approach, despite a wide range of histologies and clinical outcomes.

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The radiosensitivity index has demonstrated that soft tissue sarcomas are in general radioresistant, however exhibit a wide range of radiosensitivity.

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These differences in radiosensitivity are associated with decreased locoregional control in patients with radioresistant histologies.

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Using the radiosensitivity index we identify specific histologies of soft tissue sarcoma that may be more radioresistant, and suggest a genomic-based radiation dosing framework.

Background

Soft-tissue sarcomas (STS) are heterogeneous with variable response to radiation therapy (RT). Utilizing the radiosensitivity index (RSI) we estimated the radiobiologic ratio of lethal to sublethal damage (α/β), genomic-adjusted radiation dose(GARD), and in-turn a biological effective radiation dose (BED).

Methods

Two independent cohorts of patients with soft-tissue sarcoma were identified. The first cohort included 217 genomically-profiled samples from our institutional prospective tissue collection protocol; RSI was calculated for these samples, which were then used to dichotomize the population as either highly radioresistant (HRR) or conventionally radioresistant (CRR). In addition, RSI was used to calculate α/β ratio and GARD, providing ideal dosing based on sarcoma genomic radiosensitivity. A second cohort comprising 399 non-metastatic-STS patients treated with neoadjuvant RT and surgery was used to validate our findings.

Results

Based on the RSI of the sample cohort, 84% would historically be considered radioresistant. We identified a HRR subset that had a significant difference in the RSI, and clinically a lower tumor response to radiation (2.4% vs. 19.4%), 5-year locoregional-control (76.5% vs. 90.8%), and lower estimated α/β (3.29 vs. 5.98), when compared to CRR sarcoma. Using GARD, the dose required to optimize outcome in the HRR subset is a BED_α/β=3.29 of 97 Gy.

Conclusions

We demonstrate that on a genomic scale, that although STS is radioresistant overall, they are heterogeneous in terms of radiosensitivity. We validated this clinically and estimated an α/β ratio and dosing that would optimize outcome, personalizing dose.

Identification of a five gene signature to predict time to biochemical recurrence after radical prostatectomy

BACKGROUND

Identification of novel biomarkers associated with high-risk prostate cancer or biochemical recurrence can drive improvement in detection, prognosis, and treatment. However, studies can be limited by small sample sizes and sparse clinical follow-up data. We utilized a large sample of prostate specimens to identify a predictive model of biochemical recurrence following radical prostatectomy and we validated this model in two external data sets.

METHODS

We analyzed prostate specimens from patients undergoing radical prostatectomy at Hartford Hospital between 2008 and 2011. RNA isolated from formalin-fixed paraffin-embedded prostates was hybridized to a custom Affymetrix microarray. Regularized (least absolute shrinkage and selection operator [Lasso]) Cox regression was performed with cross-validation to identify a model that incorporated gene expression and clinical factors to predict biochemical recurrence, defined as postoperative prostate-specific antigen (PSA) > 0.2 ng/ml or receipt of triggered salvage treatment. Model performance was assessed using time-dependent receiver operating curve (ROC) curves and survival plots.

RESULTS

A total of 606 prostate specimens with gene expression and both pre- and postoperative PSA data were available for analysis. We identified a model that included Gleason grade and stage as well as five genes (CNRIP1, endoplasmic reticulum protein 44 [ERP44], metaxin-2 [MTX2], Ras homolog family member U [RHOU], and OXR1). Using the Lasso method, we determined that the five gene model independently predicted biochemical recurrence better than a model that included Gleason grade and tumor stage alone. The time-dependent ROCAUC for the five gene signature including Gleason grade and tumor stage was 0.868 compared to an AUC of 0.767 when Gleason grade and tumor stage were included alone. Low and high-risk groups displayed significant differences in their recurrence-free survival curves. The predictive model was subsequently validated on two independent data sets identified through the Gene Expression Omnibus. The model included genes (RHOU, MTX2, and ERP44) that have previously been implicated in prostate cancer biology.

CONCLUSIONS

Expression of a small number of genes is associated with an increased risk of biochemical recurrence independent of classical pathological hallmarks.

Morphologic and molecular correlates of EZH2 as a predictor of platinum resistance in high-grade ovarian serous carcinoma

BACKGROUND

Enhancer of zesta homologue 2 (EZH2) is an essential component of polycomb repressive complex 2 (PRC2) that contributes to tumor progression and chemo-resistance. The aim of this study was to comprehensively assess the prognostic value of EZH2 across the morphologic and molecular spectra of high-grade serous ovarian carcinoma (HGSOC) by utilizing both immunohistochemistry (IHC) and proteogenomic technologies.

METHODS

IHC of EZH2 was performed using a tissue microarray of 79 HGSOC scored (+/-) for lymphovascular invasion (LVI), tumor-infiltrating lymphocytic aggregates ≥1 mm (TIL) and architectural growth patterns. The association of EZH2 H-score with response to therapy and overall survival was evaluated by tumor features. We also evaluated EZH2 transcriptional (RNA sequencing) and protein (mass spectrometry) expression from bulk tumor samples from 336 HGSOC from The Cancer Genome Atlas (TCGA). EZH2 expression and co-expression networks were compared by clinical outcomes.

RESULTS

For HGSOC without TIL (58%), EZH2 expression was almost 2-fold higher in platinum resistant tumors (P = 0.01). Conversely, EZH2 was not associated with platinum resistance among TIL+ HGSOC (P = 0.41). EZH2 expression was associated with reduced survival for tumors with LVI (P = 0.04). Analysis of TCGA found higher EZH2 expression in immunoreactive and proliferative tumors (P = 6.7 × 10^- 5) although protein levels were similar across molecular subtypes (P = 0.52). Both mRNA and protein levels of EZH2 were lower in platinum resistant tumors although they were not associated with survival. Co-expression analysis revealed EZH2 networks totaling 1049 mRNA and 448 proteins that were exclusive to platinum sensitive or resistant tumors. The EZH2 network in resistant HGSOC included CARM1 which was positively correlated with EZH2 at both mRNA (r = 0.33, p = 0.003) and protein (r = 0.14, P = 0.01) levels. Further, EZH2 co-expression with CARM1 corresponded to a decreased prognostic significance of EZH2 expression in resistant tumors.

CONCLUSIONS

Our findings demonstrate that EZH2 expression varies based on its interactions with immunologic pathways and tumor microenvironment, impacting the prognostic interpretation. The association between high EZH2 expression and platinum resistance in TIL- HGSOC warrants further study of the implications for therapeutic strategies.

Diabetes, Body Fatness, and Insulin Prescription Among Adolescents and Young Adults with Cancer

Purpose: Rates of obesity and obesity-related health consequences, including type 2 diabetes (T2D) and cancer, continue to rise. While cancer patients are at an increased risk of developing T2D, the prevalence of T2D and insulin prescription among young patients with cancer remains unknown. Methods: Using the Total Cancer Care Study cohort at Huntsman Cancer Institute (Salt Lake City, UT), we identified individuals age 18-39 years at cancer diagnosis between 2009 and 2019. Multivariable logistic regression was used to investigate associations between body mass index (BMI) with insulin prescription within 1 year of cancer diagnosis. Results: In total, 344 adolescents and young adults (AYAs) were diagnosed with primary invasive cancer. Within this cohort, 19 patients (5.5%) were ever diagnosed with T2D, 48 AYAs ever received an insulin prescription (14.0%), and 197 were overweight or obese (BMI: 25+ kg/m2) at cancer diagnosis. Each kg/m2 unit increase in BMI was associated with 6% increased odds of first insulin prescription within 1 year of cancer diagnosis among AYAs, even after adjustment for age, sex, smoking history, marital status, glucocorticoid prescription, and cancer treatments (odds ratio = 1.06, 95% confidence interval 1.02-1.11; p = 0.005). Conclusion: One in every 18 AYAs with cancer ever had T2D, 1 in 7 AYA patients with cancer ever received an insulin prescription, and higher BMI was associated with increased risk of insulin prescription within a year of cancer diagnosis among AYAs. Understanding the incidence of T2D and insulin prescription/use is critical for short-term and long-term clinical management of AYAs with cancer.

Tumor immune infiltration estimated from gene expression profiles predicts colorectal cancer relapse

A substantial fraction of patients with stage I-III colorectal adenocarcinoma (CRC) experience disease relapse after surgery with curative intent. However, biomarkers for predicting the likelihood of CRC relapse have not been fully explored. Therefore, we assessed the association between tumor infiltration by a broad array of innate and adaptive immune cell types and CRC relapse risk. We implemented a discovery-validation design including a discovery dataset from Moffitt Cancer Center (MCC; Tampa, FL) and three independent validation datasets: (1) GSE41258 (2) the Molecular Epidemiology of Colorectal Cancer (MECC) study, and (3) GSE39582. Infiltration by 22 immune cell types was inferred from tumor gene expression data, and the association between immune infiltration by each cell type and relapse-free survival was assessed using Cox proportional hazards regression. Within each of the four independent cohorts, CD4+ memory activated T cell (HR: 0.93, 95% CI: 0.90-0.96; FDR = 0.0001) infiltration was associated with longer time to disease relapse, independent of stage, microsatellite instability, and adjuvant therapy. Based on our meta-analysis across the four datasets, 10 innate and adaptive immune cell types associated with disease relapse of which 2 were internally validated using multiplex immunofluorescence. Moreover, immune cell type infiltration was a better predictors of disease relapse than Consensus Molecular Subtype (CMS) and other expression-based biomarkers (Immune-AICMCC:238.1-238.9; CMS-AICMCC: 241.0). These data suggest that transcriptome-derived immune profiles are prognostic indicators of CRC relapse and quantification of both innate and adaptive immune cell types may serve as candidate biomarkers for predicting prognosis and guiding frequency and modality of disease surveillance.

Personalizing Radiotherapy Prescription Dose Using Genomic Markers of Radiosensitivity and Normal Tissue Toxicity in NSCLC

INTRODUCTION

Cancer sequencing efforts have revealed that cancer is the most complex and heterogeneous disease that affects humans. However, radiation therapy (RT), one of the most common cancer treatments, is prescribed on the basis of an empirical one-size-fits-all approach. We propose that the field of radiation oncology is operating under an outdated null hypothesis: that all patients are biologically similar and should uniformly respond to the same dose of radiation.

METHODS

We have previously developed the genomic-adjusted radiation dose, a method that accounts for biological heterogeneity and can be used to predict optimal RT dose for an individual patient. In this article, we use genomic-adjusted radiation dose to characterize the biological imprecision of one-size-fits-all RT dosing schemes that result in both over- and under-dosing for most patients treated with RT. To elucidate this inefficiency, and therefore the opportunity for improvement using a personalized dosing scheme, we develop a patient-specific competing hazards style mathematical model combining the canonical equations for tumor control probability and normal tissue complication probability. This model simultaneously optimizes tumor control and toxicity by personalizing RT dose using patient-specific genomics.

RESULTS

Using data from two prospectively collected cohorts of patients with NSCLC, we validate the competing hazards model by revealing that it predicts the results of RTOG 0617. We report how the failure of RTOG 0617 can be explained by the biological imprecision of empirical uniform dose escalation which results in 80% of patients being overexposed to normal tissue toxicity without potential tumor control benefit.

CONCLUSIONS

Our data reveal a tapestry of radiosensitivity heterogeneity, provide a biological framework that explains the failure of empirical RT dose escalation, and quantify the opportunity to improve clinical outcomes in lung cancer by incorporating genomics into RT.

TMPRSS2-ERG fusion impacts anterior tumor location in men with prostate cancer

BACKGROUND

In prostate cancer (PCa), lack of androgen receptor (AR) regulated TMPRSS2-ETS-related gene (ERG) gene fusion (ERG^negative ) status has been associated with African American race; however, the implications of ERG status for the location of dominant tumors within the prostate remains understudied.

METHODS

An African American-enriched multiinstitutional cohort of 726 PCa patients consisting of both African American men (AAM; n = 254) and European American men (EAM; n = 472) was used in the analyses. Methods of categorical analysis were used. Messenger RNA (mRNA) expression differences between anterior and posterior tumor lesions were analyzed using Wilcoxon rank-sum tests with multiple comparison corrections.

RESULTS

Anti-ERG immunohistochemistry staining showed that the association between ERG status and anterior tumors is independent of race and is consistently robust for both AAM (ERG^negative 81.4% vs. ERG^positive 18.6%; p = .005) and EAM (ERG^negative 60.4% vs. ERG^positive 39.6%; p < .001). In a multivariable model, anterior tumors were more likely to be IHC-ERG^negative (odds ratio [OR]: 3.20; 95% confidence interval [CI]: 2.14-4.78; p < .001). IHC-ERG^negative were also more likely to have high-grade tumors (OR: 1.73; 95% CI: 1.06-2.82; p = .02). In the exploratory genomic analysis, mRNA expression of location-dependent genes is highly influenced by ERG status and African American race. However, tumor location did not impact the expression of AR or the major canonical AR-target genes (KLK3, AMACR, and MYC).

CONCLUSIONS

ERG^negative tumor status is the strongest predictor of anterior prostate tumors, regardless of race. Furthermore, AR expression and canonical AR signaling do not impact tumor location.

Development and Optimization of Clinical Informatics Infrastructure to Support Bioinformatics at an Oncology Center

Translational bioinformatics for therapeutic discovery requires the infrastructure of clinical informatics. In this chapter, we describe the clinical informatics components needed for successful implementation of translational research at a cancer center. This chapter is meant to be an introduction to those clinical informatics concepts that are needed for translational research. For a detailed account of clinical informatics, the authors will guide the reader to comprehensive resources. We provide examples of workflows from Moffitt Cancer Center led by Drs. Perkins and Markowitz. This perspective represents an interesting collaboration as Dr. Perkins is the Chief Medical Information Officer and Dr. Markowitz is a translational researcher in Melanoma with an active informatics component to his laboratory to study the mechanisms of resistance to checkpoint blockade and an active member of the clinical informatics team.

DACH1 mutation frequency in endometrial cancer is associated with high tumor mutation burden

Objective

DACH1 is a transcriptional repressor and tumor suppressor gene frequently mutated in melanoma, bladder, and prostate cancer. Loss of DACH1 expression is associated with poor prognostic features and reduced overall survival in uterine cancer. In this study, we utilized the Oncology Research Information Exchange Network (ORIEN) Avatar database to determine the frequency of DACH1 mutations in patients with endometrial cancer in our Kentucky population.

Methods

We obtained clinical and genomic data for 65 patients with endometrial cancer from the Markey Cancer Center (MCC). We examined the clinical attributes of the cancers by DACH1 status by comparing whole-exome sequencing (WES), RNA Sequencing (RNASeq), microsatellite instability (MSI), and tumor mutational burden (TMB).

Results

Kentucky women with endometrial cancer had an increased frequency of DACH1 mutations (12/65 patients, 18.5%) compared to The Cancer Genome Atlas (TCGA) endometrial cancer population (25/586 patients, 3.8%) with p-value = 1.04E-05. DACH1 mutations were associated with increased tumor mutation count in both TCGA (median 65 vs. 8972, p-value = 7.35E-09) and our Kentucky population (490 vs. 2160, p-value = 6.0E-04). DACH1 mutated patients have a higher tumor mutation burden compared to DACH1 wild-type (24 vs. 6.02, p-value = 4.29E-05). DACH1 mutations showed significant gene co-occurrence patterns with POLE, MLH1, and PMS2. DACH1 mutations were not associated with an increase in microsatellite instability at MCC (MSI-H) (p-value = 0.1342).

Conclusions

DACH1 mutations are prevalent in Kentucky patients with endometrial cancer. These mutations are associated with high tumor mutational burden and co-occur with genome destabilizing gene mutations. These findings suggest DACH1 may be a candidate biomarker for future trials with immunotherapy, particularly in endometrial cancers.

Primary tumors from mucosal barrier organs drive unique eosinophil infiltration patterns and clinical associations

Eosinophils are bone marrow-derived granulocytes that display key effector functions in allergic diseases. Nonetheless, recent data highlight important roles for eosinophils in the tumor microenvironment (TME). Eosinophils have been attributed with pleiotropic and perhaps conflicting functions, which may be attributed at least in part to variations in eosinophil quantitation in the TME. Thus, a reliable, quantitative, and robust method for the assessment of eosinophilic infiltration in the TME is required. This type of methodology could standardize the identification of these cells and promote the subsequent generation of hypothesis-driven mechanistic studies. To this end, we conducted a comprehensive analysis of multiple primary tumors from distinct anatomical sites using a standardized method. Bioinformatics analysis of 10,469 genomically profiled primary tumors revealed that eosinophil abundance within different tumors can be categorized into three groups representing tumors with high, intermediate, and low eosinophil levels. Consequently, eosinophil abundance, as well as spatial distribution, was determined in tissue tumor arrays of six tumors representing all three classifications (colon and esophagus - high; lung - intermediate; cervix, ovary, and breast - low). With the exception of breast cancer, eosinophils were mainly localized in the tumor stroma. Importantly, the tumor anatomical site was identified as the primary predictive factor of eosinophil stromal density highlighting a distinction between mucosal-barrier organs versus non-mucosal barrier organs. These findings enhance our understanding of eosinophil diversity in the TME and provide a compelling rationale for future experiments assessing the activity of these cells.

Factors Predicting Participation in the Prospective Genomic Sequencing Study, Total Cancer Care (TCC), in Kentucky

PURPOSE

Large-scale genomic sequencing studies are driving oncology drug development. However, rural populations, like those residing in Appalachian Kentucky, are underrepresented in these efforts. In this study, we determined the frequency of participation, reasons for nonparticipation, and factors predicting the decision to participate in the Total Cancer Care (TCC) prospective genomic cohort study.

METHODS

A total of 1,188 patients were invited to enroll in the TCC prospective cohort from December 2018 to May 2019. Declining patients were queried for their rationale for nonparticipation and their patient data were obtained from the Kentucky Cancer Registry (KCR). Logistic regression was used to assess the association between characteristics and study participation. The association of study participation with survival was modeled with Cox proportional-hazards regression.

RESULTS

90.9% (1,081) patients consented to participate. In multivariate analysis, factors significantly associated with participation were age, gender, treatment status, and race. Though overall more women participated in the study, men were more likely to participate than women when invited (OR 1.57). Younger, Caucasian individuals who had received chemotherapy, but not surgery, were also more likely to participate. Patients in the Kentucky Appalachian cohort were primarily rural, had less educational attainment, and lower socioeconomic status. Kentucky Appalachian patients were no less likely to enroll in TCC than non-Appalachian patients. Consented individuals had higher overall survival compared to those who declined.

CONCLUSION

Though minorities, those with low socioeconomic status, and rural populations are underrepresented in genomic studies, they were no less likely to participate when given the opportunity, and participation was associated with better clinical outcomes.

Aberrant Epidermal Growth Factor Receptor RNA Splice Products Are Among the Most Frequent Somatic Alterations in Clear Cell Renal Cell Carcinoma and Are Associated with a Poor Response to Immunotherapy

BACKGROUND

Accumulating evidence suggests that alternative RNA splicing has an important role in cancer development and progression by driving the expression of a diverse array of RNA and protein isoforms from a handful of genes. However, our understanding of the clinical significance of cancer-specific RNA splicing in renal cell carcinoma (RCC) is limited.

OBJECTIVE

To characterize and validate a novel oncogene RNA splicing event discovered in patients with RCC and to correlate expression with clinical outcomes.

DESIGN, SETTING, AND PARTICIPANTS

Using DNA and RNA sequencing, we identified a novel epidermal growth factor receptor (EGFR) splicing alteration (EGFR_pr20CTF) in RCC tumor tissue.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We confirmed the frequency and specificity of the EGFR_pr20CTF variant by analyzing cohorts of patients from our institution (n = 699) and The Cancer Genome Atlas (TCGA; n = 832). Furthermore, we analyzed its expression in tumor tissue and a human kidney cancer cell line using reverse transcriptase-polymerase chain reaction. Variant expression was also correlated with survival and response to systemic therapy.

RESULTS AND LIMITATIONS

EGFR_pr20CTF expression was identified in 71.7% (n = 71/99) of patients with RCC in our institutional cohort and in 56.7% (n = 279/492) of patients in the TCGA cohort. EGFR_pr20CTF was found to be specific to clear cell renal cell carcinoma (ccRCC), occurring in <0.2% of non-RCC tumors (n = 2/1091). High levels of EGFR_pr20CTF correlated with lower survival at 48 mo following immunotherapy (p = 0.036). The average survival in patients with high EGFR_pr20CTF expression was <16 mo.

CONCLUSIONS

The EGFR_pr20CTF RNA splice variant occurs frequently, is specific to patients with advanced ccRCC, and is associated with a poor response to immunotherapy.

PATIENT SUMMARY

Cancer-specific RNA alternative splicing may portend a poor prognosis in patients with advanced clear cell renal cell carcinoma. Further investigation will help clarify whether EGFR_pr20CTF can be used as a biomarker for this patient population.

Alterations in genetic pathways following radiotherapy for head and neck cancer

BACKGROUND

Radiotherapy (RT) is an integral component in the treatment of head and neck cancer (HNC).We hypothesized there would be alterations in gene-expression and pathway activity in HNC samples obtained in recurrent HNC that were previously treated with RT, when compared to RT-naïve disease.

METHODS

Patient data was abstracted from a prospectively maintained database. Linear-microarray analysis and supervised gene-set enrichment-analysis were employed to compare RT-naive and recurrent disease after prior-RT.

RESULTS

A total of 157 patients were analyzed, 96 (61%) were RT-naive and 61 (39%) had RT.After radiation, there was upregulation of genes associated with angiogenesis, protein-translation-machinery, cell-cycle regulation, and growth factors, and downregulation associated with Myc activity, and hypoxic response (all P < .001).Previously irradiated HNC was associated with downregulation in 19/42 genes in the Wnt/B-catenin-pathway (P = .045)and 119/199 genes involved in the MYC target pathway (P = .024).

CONCLUSION

Patients with recurrences salvaged surgically post-RT had significant alterations in gene-expression and in Wnt/B-catenin and MYC-target pathways. These pathways may represent potential targets to prevent development of resistance to RT.

Using the Radiosensitivity Index (RSI) to Predict Pelvic Failure in Endometrial Cancer Treated With Adjuvant Radiation Therapy

PURPOSE

Variability exists in the adjuvant treatment for endometrial cancer (EC) based on surgical pathology and institutional preference. The radiosensitivity index (RSI) is a previously validated multigene expression index that estimates tumor radiosensitivity. We evaluate RSI as a genomic predictor for pelvic failure (PF) in EC patients treated with adjuvant radiation therapy (RT).

METHODS AND MATERIALS

Using our institutional tissue biorepository, we identified EC patients treated between January 1999 and April 2011 with primarily endometrioid histology (n = 176; 86%) who received various adjuvant therapies. The RSI 10-gene signature was calculated for each sample using the previously published algorithm. Radiophenotype was determined using the previously identified cutpoint where RSI ≥ 0.375 denotes radioresistance (RR) and RSI < 0.375 describes radiosensitivity.

RESULTS

A total of 204 patients were identified, of which 83 (41%) were treated with adjuvant RT. Median follow-up was 38.5 months. All patients underwent hysterectomy with bilateral salpingo-oophorectomy with the majority undergoing lymph node dissection (n = 181; 88%). In patients treated with radiation, RR tumors were more likely to experience PF (3-year pelvic control 84% vs 100%; P = .02) with worse PF-free survival (PFFS) (3-year PFFS 65% vs 89%; P = .04). Furthermore, in the patients who did not receive RT, there was no difference in PF (P = .87) or PFFS (P = .57) between the RR/radiosensitive tumors. On multivariable analysis, factors that continued to predict for PF included the RR phenotype (hazard ratio [HR], 12.2; P = .003), lymph node involvement (HR, 4.4; P = .02), and serosal or adnexal involvement (HR, 5.3; P = .01).

CONCLUSIONS

On multivariable analysis, RSI was found to be a significant predictor of PF in patients treated with adjuvant RT. We propose using RSI to predict which patients are at higher risk for failing in the pelvis and may be candidates for treatment escalation in the adjuvant setting.

A Molecular Epidemiological Analysis Of Programmed Cell Death Ligand-1 (PD-L1) Protein Expression, Mutations And Survival In Non-Small Cell Lung Cancer

Purpose

To characterize programmed cell death ligand-1 (PD-L1) expression in relation to survival and gene mutation status in patients with advanced NSCLC. The study also explored the influence of tumor mutational burden (TMB) on PD-L1 expression and patient characteristics.

Patients and methods

Adult patients with histologically or cytologically documented Stage IIIB/Stage IV/recurrent/progressive NSCLC, Eastern Cooperative Oncology Group performance status 0 to 3, and >2 lines of prior systemic treatment regimens were included in this retrospective analysis. Patients were treated from 1997 to 2015 at H. Lee Moffitt Cancer Center and Research Institute, Tampa, or at 7 community centers across the United States. PD-L1 expression level was determined using the VENTANA PD-L1 (SP263) Assay. EGFR and KRAS mutation status and ALK rearrangements were determined by targeted DNA sequencing; these were obtained from clinical records where targeted DNA sequencing was not performed. TMB was calculated as the total number of somatic mutations per sample.

Results

From a total of 136 patients included in the study, 23.5% had tumors with high PD-L1 expression (≥25%). There were no significant differences in patient characteristics, overall survival (OS), and progression-free survival (PFS) between patients with high PD-L1 expression (median OS: 39.5 months; median PFS: 15.8 months) vs low PD-L1 expression (<25%; median OS: 38.1 months; median PFS: 18.6 months). PD-L1 expression level correlated (P=0.05) with TMB and was consistent with The Cancer Genome Atlas data.

Conclusion

In this retrospective analysis, survival outcomes of patients with advanced NSCLC were comparable by PD-L1 expression level. EGFR and KRAS mutation status were not found to be significantly associated with PD-L1 expression level, while TMB was weakly associated with PD-L1 expression level. Overall, PD-L1 expression level was not observed to be an independent prognostic biomarker in this cohort of patients with advanced NSCLC treated with chemotherapy.

Transcriptomic Differences between Primary Colorectal Adenocarcinomas and Distant Metastases Reveal Metastatic Colorectal Cancer Subtypes

Approximately 20% of colorectal cancer patients with colorectal adenocarcinomas present with metastases at the time of diagnosis, and therapies that specially target these metastases are lacking. We present a novel approach for investigating transcriptomic differences between primary colorectal adenocarcinoma and distant metastases, which may help to identify primary tumors with high risk for future dissemination and to inform the development of metastasis-targeted therapies. To effectively compare the transcriptomes of primary colorectal adenocarcinoma and metastatic lesions at both the gene and pathway levels, we eliminated tissue specificity of the "host" organs where tumors are located and adjusted for confounders such as exposure to chemotherapy and radiation, and identified that metastases were characterized by reduced epithelial-mesenchymal transition (EMT) but increased MYC target and DNA-repair pathway activities. FBN2 and MMP3 were the most differentially expressed genes between primary tumors and metastases. The two subtypes of colorectal adenocarcinoma metastases that were identified, EMT inflammatory and proliferative, were distinct from the consensus molecular subtype (CMS) 3, suggesting subtype exclusivity. In summary, this study highlights transcriptomic differences between primary tumors and colorectal adenocarcinoma metastases and delineates pathways that are activated in metastases that could be targeted in colorectal adenocarcinoma patients with metastatic disease. SIGNIFICANCE: These findings identify a colorectal adenocarcinoma metastasis-specific gene-expression signature that is free from potentially confounding background signals coming from treatment exposure and the normal host tissue that the metastasis is now situated within.

Utilizing the genomically adjusted radiation dose (GARD) to personalize adjuvant radiotherapy in triple negative breast cancer management

Background

Utilizing the linear quadratic model and the radiosensitivity index (RSI), we have derived an expression for the genomically adjusted radiation dose (GARD) to model radiation dose effect. We hypothesize GARD is associated with local recurrence and can be used to optimize individual triple negative breast cancer (TNBC) radiation dose.

Methods

TN patients from two independent datasets were assessed. The first cohort consisted of 58 patients treated at 5 European centers with breast conservation surgery followed by adjuvant radiotherapy (RT). The second dataset consisted of 55 patients treated with adjuvant radiation therapy.

Findings

In cohort 1, multivariable analysis revealed that as a dichotomous variable (HR: 2.5 95% CI 1–7.1; p = .05), GARD was associated with local control. This was confirmed in the second independent dataset where GARD was the only significant factor associated with local control (HR: 4.4 95% CI 1.1–29.5; p = .04). We utilized GARD to calculate an individualized radiation dose for each TN patient in cohort 2 by determining the physical dose required to achieve the GARD target value (GARD ≥ 21). While 7% of patients were optimized with a dose of 30 Gy, 91% of patients would be optimized with 70 Gy.

Interpretation

GARD is associated with local control following whole breast or post-mastectomy radiotherapy (RT) in TN patients. By modeling RT dose effect with GARD, we demonstrate that no single dose is optimal for all patients and propose the first dose range to optimize RT at an individual patient level in TNBC.

Repurposing EGFR Inhibitor Utility in Colorectal Cancer in Mutant APC and TP53 Subpopulations

BACKGROUND

EGFR is a major therapeutic target for colorectal cancer. Currently, extended RAS/RAF testing identifies only nonresponders to EGFR inhibitors (EGFRi). We aimed to develop a mutation signature that further refines drug-sensitive subpopulations to improve EGFRi outcomes.

METHODS

A prespecified, 203-gene expression signature score measuring cetuximab sensitivity (CTX-S) was validated with two independent clinical trial datasets of cetuximab-treated patients with colorectal cancer (n = 44 and n = 80) as well as an in vitro dataset of 147 cell lines. The CTX-S score was then used to decipher mutated genes that predict EGFRi sensitivity. The predictive value of the identified mutation signature was further validated by additional independent datasets.

RESULTS

Here, we report the discovery of a 2-gene (APC+TP53) mutation signature that was useful in identifying EGFRi-sensitive colorectal cancer subpopulations. Mutant APC+TP53 tumors were more predominant in left- versus right-sided colorectal cancers (52% vs. 21%, P = 0.0004), in microsatellite stable (MSS) versus microsatellite instable (MSI) cases (47% vs. 2%, P < 0.0001), and in the consensus molecular subtype 2 versus others (75% vs. 37%, P < 0.0001). Moreover, mutant APC+TP53 tumors had favorable outcomes in two cetuximab-treated patient-derived tumor xenograft (PDX) datasets (P = 0.0277, n = 52; P = 0.0008, n = 98).

CONCLUSIONS

Our findings suggest that the APC and TP53 combination mutation may account for the laterality of EGFRi sensitivity and provide a rationale for refining treated populations. The results also suggest addition of APC+TP53 sequencing to extended RAS/RAF testing that may directly increase the response rates of EGFRi therapy in selected patients.

IMPACT

These findings, if further validated through clinical trials, could also expand the utility of EGFRi therapies that are currently underutilized.