Integrative pan-cancer genomic and transcriptomic analyses of refractory metastatic cancer

NCI Cancer Research Data Commons: Cloud-Based Analytic Resources

The NCI's Cloud Resources (CR) are the analytical components of the Cancer Research Data Commons (CRDC) ecosystem. This review describes how the three CRs (Broad Institute FireCloud, Institute for Systems Biology Cancer Gateway in the Cloud, and Seven Bridges Cancer Genomics Cloud) provide access and availability to large, cloud-hosted, multimodal cancer datasets, as well as offer tools and workspaces for performing data analysis where the data resides, without download or storage. In addition, users can upload their own data and tools into their workspaces, allowing researchers to create custom analysis workflows and integrate CRDC-hosted data with their own. See related articles by Brady et al., p. 1384, Wang et al., p. 1388, and Kim et al., p. 1404.

Full-spectral genome analysis of natural killer/T cell lymphoma highlights impacts of genome instability in driving its progression

BACKGROUND

Natural killer/T cell lymphoma (NKTCL) is a clinically and genetically heterogeneous disease with poor prognosis. Genome sequencing and mutation characterization provides a powerful approach for patient stratification, treatment target discovery, and etiology identification. However, previous studies mostly concentrated on base-level mutations in primary NKTCL, whereas the large-scale genomic alterations in NKTCL and the mutational landscapes in relapsed/refractory NKTCL remain largely unexplored.

METHODS

Here, we assembled whole-genome sequencing and whole-exome sequencing data from 163 patients with primary or relapsed/refractory NKTCL and compared their somatic mutational landscapes at both nucleotide and structure levels.

RESULTS

Our study not only confirmed previously reported common NKTCL mutational targets like STAT3, TP53, and DDX3X but also unveiled several novel high-frequency mutational targets such as PRDM9, DST, and RBMX. In terms of the overall mutational landscape, we observed striking differences between primary and relapsed/refractory NKTCL patient groups, with the latter exhibits higher levels of tumor mutation burden, copy number variants (CNVs), and structural variants (SVs), indicating a strong signal of genomic instability. Complex structural rearrangements such as chromothripsis and focal amplification are also significantly enriched in relapsed/refractory NKTCL patients, exerting a substantial impact on prognosis. Accordingly, we devised a novel molecular subtyping system (i.e., C0-C4) with distinct prognosis by integrating potential driver mutations at both nucleotide and structural levels, which further provides an informative guidance for novel treatments that target these specific driver mutations and genome instability as a whole.

CONCLUSIONS

The striking differences underlying the mutational landscapes between the primary and relapsed/refractory NKTCL patients highlight the importance of genomic instability in driving the progression of NKTCL. Our newly proposed molecular subtyping system is valuable in assisting patient stratification and novel treatment design towards a better prognosis in the age of precision medicine.

The two sides of chromosomal instability: drivers and brakes in cancer

Chromosomal instability (CIN) is a hallmark of cancer and is associated with tumor cell malignancy. CIN triggers a chain reaction in cells leading to chromosomal abnormalities, including deviations from the normal chromosome number or structural changes in chromosomes. CIN arises from errors in DNA replication and chromosome segregation during cell division, leading to the formation of cells with abnormal number and/or structure of chromosomes. Errors in DNA replication result from abnormal replication licensing as well as replication stress, such as double-strand breaks and stalled replication forks; meanwhile, errors in chromosome segregation stem from defects in chromosome segregation machinery, including centrosome amplification, erroneous microtubule-kinetochore attachments, spindle assembly checkpoint, or defective sister chromatids cohesion. In normal cells, CIN is deleterious and is associated with DNA damage, proteotoxic stress, metabolic alteration, cell cycle arrest, and senescence. Paradoxically, despite these negative consequences, CIN is one of the hallmarks of cancer found in over 90% of solid tumors and in blood cancers. Furthermore, CIN could endow tumors with enhanced adaptation capabilities due to increased intratumor heterogeneity, thereby facilitating adaptive resistance to therapies; however, excessive CIN could induce tumor cells death, leading to the "just-right" model for CIN in tumors. Elucidating the complex nature of CIN is crucial for understanding the dynamics of tumorigenesis and for developing effective anti-tumor treatments. This review provides an overview of causes and consequences of CIN, as well as the paradox of CIN, a phenomenon that continues to perplex researchers. Finally, this review explores the potential of CIN-based anti-tumor therapy.

Moving toward precision medicine to predict drug sensitivity in patients with metastatic breast cancer

Tumor heterogeneity represents a major challenge in breast cancer, being associated with disease progression and treatment resistance. Precision medicine has been extensively applied to dissect tumor heterogeneity and, through a deeper molecular understanding of the disease, to personalize therapeutic strategies. In the last years, technological advances have widely improved the understanding of breast cancer biology and several trials have been developed to translate these new insights into clinical practice, with the ultimate aim of improving patients' outcomes. In the era of molecular oncology, genomics analyses and other methodologies are shaping a new treatment algorithm in breast cancer care. In this manuscript, we review the main steps of precision medicine to predict drug sensitivity in breast cancer from a translational point of view. Genomic developments and their clinical implications are discussed, along with technological advancements that could broaden precision medicine applications. Current achievements are put into perspective to provide an overview of the state-of-art of breast cancer precision oncology as well as to identify future research directions.

Initial management approach for localized/locally advanced disease is critical to guide metastatic castration-resistant prostate cancer care

BACKGROUND

Currently, several therapies are available for metastatic castration-resistant prostate cancer (mCRPC) but no specific clinical factors to personalize treatment. We first sought the prognostic value of duration on androgen-deprivation therapy (ADT) for hormone-sensitive prostate cancer (HSPC) in patients receiving androgen-receptor-signaling inhibitors (ARSI) for mCRPC.

METHODS

A multicenter cohort of mCRPC patients who started ARSI between July 2011 and October 2021 was identified. Based on their initial disease burden and duration on ADT for HSPC, primary progressive (PP) men were classified into four groups: low/intermediate-risk localized disease (LOC) and high-risk localized/locally advanced disease (LAD) and short-term (ST) < 24 vs. long-term (LT) ADT ≥ 24 months, whereas de novo (DN) mHSPC were subdivided into short-time vs. long-time to CRPC.

RESULTS

We included 919 mCRPC patients with a median age of 77 years [interquartile range (IQR) = 71-82)]. Median ADT duration in HSPC was 24 months (IQR = 14-40). Median follow-up was 91 months (IQR = 62-138), median OS and PFS from ARSI start were 20 (IQR 10-32) and 10 months (IQR = 5-19), respectively. In PP developing metastatic disease (n = 655, 71.3%), LOC and LAD with ST ADT had a greater than almost double-risk of death compared to LT ADT (LOC/ST: hazard ratio [HR] = 2.01; 95% CI 1.54-2.64; LAD/ST: HR = 1.73; 95% CI 1.34-2.24; p < 0.001). In the multivariate analysis including age, prognostic cohort, Gleason, ECOG, radical radiotherapy and prostatectomy, groups with ST ADT were associated with worse OS compared to LT ADT (LOC/ST: HR = 1.84; 95% CI 1.38-2.45; p < 0.001; LAD/ST: HR = 1.59; 95% CI 1.21-2.10; p < 0.001), along with ECOG > 2 (HR = 1.55; 95% CI 1.06-2.26; p = 0.03). There were also similar results of PFS. Moreover, long-time to CRPC in patients with history of DN mHSPC (n = 264, 28.7%) resulted in a better OS/PFS (HR = 0.76, 95% CI 0.56-1.02, p = 0.064 and HR = 0.74, 95% CI 0.55-0.99, p = 0.042, respectively).

CONCLUSIONS

Our study showed that duration on ADT for mHSPC was significantly associated with survival in mCRPC undergoing ARSI. These findings suggest a possible connection between initial management of prostate tumour and a better prognostication in mCRPC. Prospective trials are warranted.

Machine learning and bioinformatic analyses link the cell surface receptor transcript levels to the drug response of breast cancer cells and drug off-target effects

Breast cancer responds variably to anticancer therapies, often leading to significant off-target effects. This study proposes that the variability in tumour responses and drug-induced adverse events is linked to the transcriptional profiles of cell surface receptors (CSRs) in breast tumours and normal tissues. We analysed multiple datasets to compare CSR expression in breast tumours with that in non-cancerous human tissues. Our findings correlate the drug responses of breast cancer cell lines with the expression levels of their targeted CSRs. Notably, we identified distinct differences in CSR expression between primary breast tumour subtypes and corresponding cell lines, which may influence drug response predictions. Additionally, we used clinical trial data to uncover associations between CSR gene expression in healthy tissues and the incidence of adverse drug reactions. This integrative approach facilitates the selection of optimal CSR targets for therapy, leveraging cell line dose-responses, CSR expression in normal tissues, and patient adverse event profiles.

Identification of ACBD3 as a new molecular biomarker in pan-cancers through bioinformatic analysis: a preclinical study

BACKGROUND

Acyl-CoA-binding domain-containing 3 (ACBD3) is a multifunctional protein, that plays essential roles in cellular signaling and membrane domain organization. Although the precise roles of ACBD3 in various cancers remain unclear. Thus, we aimed to determine the diverse roles of ACBD3 in pan-cancers.

METHODS

Relevant clinical and RNA-sequencing data for normal tissues and 33 tumors from The Cancer Genome Atlas (TCGA) database, the Human Protein Atlas, and other databases were applied to investigate ACBD3 expression in various cancers. ACBD3-binding and ACBD3-related target genes were obtained from the STRING and GEPIA2 databases. The possible functions of ACBD3-binding genes were explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We also applied the diagnostic value and survival prognosis analysis of ACBD3 in pan-cancers using R language. The mutational features of ACBD3 in various TCGA cancers were obtained from the cBioPortal database.

RESULTS

When compared with normal tissues, ACBD3 expression was statistically upregulated in eleven cancers and downregulated in three cancers. ACBD3 expression was remarkably different among various pathological stages of tumors, immune and molecular subtypes of cancers, cancer phosphorylation levels, and immune cell infiltration. The survival of four tumors was correlated with the expression level of ACBD3, including pancreatic adenocarcinoma, adrenocortical carcinoma, sarcoma, and glioma. The high accuracy in diagnosing multiple tumors and its correlation with prognosis indicated that ACBD3 may be a potential biomarker of pan-cancers.

CONCLUSION

According to our pan-cancer analysis, ACBD3 may serve as a remarkable prognostic and diagnostic biomarker of pan-cancers as well as contribute to tumor development. ACBD3 may also provide new directions for cancer treatment targets in the future.

Therapeutic approaches in patients with bone metastasis due to endometrial carcinoma - A systematic review

Background

Bone metastases (BM) are uncommon in endometrial carcinoma (EC), without information on the optimal oncologic management of patients with BM in EC. Here, we systematically review clinical characteristics, treatment approaches and prognosis in patients with BM in EC.

Methods

We conducted a systematic literature search until 27th March 2022 on PubMed, MEDLINE, Embase and clinicaltrials.gov. Outcomes included treatment frequency and survival after BM with comparators being treatment approaches (local cytoreductive bone surgery, systemic therapy, and local radiotherapy). Risk of bias was assessed using the NIH Quality Assessment Tool and Navigation Guide methodology.

Results

We retrieved 1096 records of which 112 retrospective studies (12 cohort studies, 12/12 fair quality; 100 case studies, 100/100 low quality) with a total of 1566 patients were included. The majority had a primary diagnosis of FIGO stage IV, grade 3 endometrioid EC. Singular BM were present in a median of 39.2%, multiple BM in 60.8% and synchronous additional distant metastases in 48.1% of patients respectively. In patients with secondary BM median time to bone recurrence was 14 months. Median survival after BM was 12 months. Local cytoreductive bone surgery was assessed in 7/13 cohorts and performed in a median of 15.8% (interquartile range [IQR] 10.3-43.0) of patients. Chemotherapy was assessed in 11/13 cohorts and administered in a median of 55.5% (IQR 41.0-63.9), hormonal therapy (7/13 cohorts) in 24.7% (IQR 16.3-36.0), and osteooncologic therapy (4/13 cohorts) in 2.7% (IQR 0.0-7.5) of patients respectively. Local radiotherapy was assessed in 9/13 cohorts and performed in a median of 66.7% (IQR 55.6-70.0) of patients. Survival benefits were seen in 2/3 cohorts after local cytoreductive bone surgery, and in 2/7 cohorts after chemotherapy without survival benefits in the remaining cohorts and investigated therapies. Limitations include the lack of controlled intervention studies, the heterogeneity and retrospective nature of the investigated populations.

Conclusions

This systematic review shows heterogenous therapeutic approaches in clinical practice without clear evidence for optimal oncologic management for patients with BM in EC.

Trastuzumab deruxtecan in metastatic breast cancer with variable HER2 expression: the phase 2 DAISY trial

The mechanisms of action of and resistance to trastuzumab deruxtecan (T-DXd), an anti-HER2-drug conjugate for breast cancer treatment, remain unclear. The phase 2 DAISY trial evaluated the efficacy of T-DXd in patients with HER2-overexpressing (n = 72, cohort 1), HER2-low (n = 74, cohort 2) and HER2 non-expressing (n = 40, cohort 3) metastatic breast cancer. In the full analysis set population (n = 177), the confirmed objective response rate (primary endpoint) was 70.6% (95% confidence interval (CI) 58.3-81) in cohort 1, 37.5% (95% CI 26.4-49.7) in cohort 2 and 29.7% (95% CI 15.9-47) in cohort 3. The primary endpoint was met in cohorts 1 and 2. Secondary endpoints included safety. No new safety signals were observed. During treatment, HER2-expressing tumors (n = 4) presented strong T-DXd staining. Conversely, HER2 immunohistochemistry 0 samples (n = 3) presented no or very few T-DXd staining (Pearson correlation coefficient r = 0.75, P = 0.053). Among patients with HER2 immunohistochemistry 0 metastatic breast cancer, 5 of 14 (35.7%, 95% CI 12.8-64.9) with ERBB2 expression below the median presented a confirmed objective response as compared to 3 of 10 (30%, 95% CI 6.7-65.2) with ERBB2 expression above the median. Although HER2 expression is a determinant of T-DXd efficacy, our study suggests that additional mechanisms may also be involved. (ClinicalTrials.gov identifier NCT04132960 .).

Insights into the metastatic cascade through research autopsies

Metastasis is a complex process and the leading cause of cancer-related death globally. Recent studies have demonstrated that genomic sequencing data from paired primary and metastatic tumours can be used to trace the evolutionary origins of cells responsible for metastasis. This approach has yielded new insights into the genomic alterations that engender metastatic potential, and the mechanisms by which cancer spreads. Given that the reliability of these approaches is contingent upon how representative the samples are of primary and metastatic tumour heterogeneity, we review insights from studies that have reconstructed the evolution of metastasis within the context of their cohorts and designs. We discuss the role of research autopsies in achieving the comprehensive sampling necessary to advance the current understanding of metastasis.