A pilot study utilizing multi-omic molecular profiling to find potential targets and select individualized treatments for patients with previously treated metastatic breast cancer

Multi-omic profiling in breast cancer: utility for advancing diagnostics and clinical care

INTRODUCTION

Breast cancer remains a major global health challenge. While advances in precision oncology have contributed to improvements in patient outcomes and provided a deeper understanding of the biological mechanisms that drive the disease, historically, research and patients' allocation to treatment have heavily relied on single-omic approaches, analyzing individual molecular dimensions such as genomics, transcriptomics, or proteomics. While these have provided deep insights into breast cancer biology, they often fail to offer a complete understanding of the disease's complex molecular landscape.

AREAS COVERED

In this review, the authors explore the recent advancements in multi-omic research in the realm of breast cancer and use clinical data to show how multi-omic integration can offer a more holistic understanding of the molecular alterations and their functional consequences underlying breast cancer.

EXPERT OPINION

The overall developments in multi-omic research and AI are expected to complement precision diagnostics through potentially refining prognostic models, and treatment selection. Overcoming challenges such as cost, data complexity, and lack of standardization is crucial for unlocking the full potential of multi-omics and AI in breast cancer patient care to enable the advancement of personalized treatments and improve patient outcomes.

Real-time functional proteomics enhances therapeutic targeting in precision oncology molecular tumor boards

Collaborative review of molecular profiling data by multidisciplinary molecular tumor boards (MTB) is increasingly important for improving patient management and outcomes, though currently relies nearly exclusively on nucleic acid next-generation sequencing (NGS) and limited panels of immunohistochemistry-based protein abundance data. We examined the feasibility of incorporating real-time laser microdissection (LMD) enrichment of tumor epithelium and commercial CLIA-based reverse phase protein array (RPPA) protein drug target expression/activation profiling into our cancer center's MTB to complement standard clinical NGS-based profiling. The LMD-RPPA workflow was performed within a therapeutically permissive timeframe with a median dwell time of nine days, during which specimens were processed outside of standard clinical workflows. The RPPA-generated data supported additional and/or alternative therapeutic considerations for 54% of profiled patients following review by the MTB. These findings suggest that integrating proteomic/phosphoproteomic and NGS-based genomic data creates opportunities to further personalize clinical decision-making for precision oncology.

Drug response-based precision therapeutic selection for tamoxifen-resistant triple-positive breast cancer

Breast cancer adaptability to the drug environment reduces the chemotherapeutic response and facilitates acquired drug resistance. Cancer-specific therapeutics can be more effective against advanced-stage cancer than standard chemotherapeutics. To extend the paradigm of cancer-specific therapeutics, clinically relevant acquired tamoxifen-resistant MCF-7 proteome was deconstructed to identify possible druggable targets (N = 150). Twenty-eight drug inhibitors were used against identified druggable targets to suppress non-resistant (NC) and resistant cells (RC). First, selected drugs were screened using growth-inhibitory response against NC and RC. Seven drugs were shortlisted for their time-dependent (10-12 days) cytotoxic effect and further narrowed to three effective drugs (e.g., cisplatin, doxorubicin, and hydroxychloroquine). The growth-suppressive effectiveness of selected drugs was validated in the complex spheroid model (progressive and regressive). In the progressive model, doxorubicin (RC: 83.64 %, NC: 54.81 %), followed by cisplatin (RC: 76.66 %, NC: 68.94 %) and hydroxychloroquine (RC: 68.70 %, NC: 61.78 %) showed a significant growth-suppressive effect. However, in fully grown regressive spheroid, after 4th drug treatment, cisplatin significantly suppressed RC (84.79 %) and NC (40.21 %), while doxorubicin and hydroxychloroquine significantly suppressed only RC (76.09 and 76.34 %). Our in-depth investigation effectively integrated the expression data with the cancer-specific therapeutic investigation. Furthermore, our three-step sequential drug-screening approach unbiasedly identified cisplatin, doxorubicin, and hydroxychloroquine as an efficacious drug to target heterogeneous cancer cell populations. SIGNIFICANCE STATEMENT: Hormonal-positive BC grows slowly, and hormonal-inhibitors effectively suppress the oncogenesis. However, development of drug-resistance not only reduces the drug-response but also increases the chance of BC aggressiveness. Further, alternative chemotherapeutics are widely used to control advanced-stage BC. In contrast, we hypothesized that, compared to standard chemotherapeutics, cancer-specific drugs can be more effective against resistant-cancer. Although cancer-specific treatment identification is an uphill battle, our work shows proteome data can be used for drug selection. We identified multiple druggable targets and, using ex-vivo methods narrowed multiple drugs to disease-condition-specific therapeutics. We consider that our investigation successfully interconnected the expression data with the functional disease-specific therapeutic investigation and selected drugs can be used for effective resistant treatment with higher therapeutic response.

Quantitative proteomic analysis of HER2 protein expression in PDAC tumors

Metastatic pancreatic adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the United States, with a 5-year survival rate of only 11%, necessitating identification of novel treatment paradigms. Tumor tissue specimens from patients with PDAC, breast cancer, and other solid tumor malignancies were collected and tumor cells were enriched using laser microdissection (LMD). Reverse phase protein array (RPPA) analysis was performed on enriched tumor cell lysates to quantify a 32-protein/phosphoprotein biomarker panel comprising known anticancer drug targets and/or cancer-related total and phosphorylated proteins, including HER2Total, HER2Y1248, and HER3Y1289. RPPA analysis revealed significant levels of HER2Total in PDAC patients at abundances comparable to HER2-positive (IHC 3+) and HER2-low (IHC 1+ /2+ , FISH-) breast cancer tissues, for which HER2 screening is routinely performed. These data support a critical unmet need for routine clinical evaluation of HER2 expression in PDAC patients and examination of the utility of HER2-directed antibody-drug conjugates in these patients.

Immune Resistance Mechanisms and the Road to Personalized Immunotherapy

What does the future of cancer immunotherapy look like and how do we get there? Find out where we've been and where we're headed in A Report on Resistance: The Road to personalized immunotherapy.

Mass spectrometry-based phosphoproteomics in clinical applications

Protein phosphorylation is an essential post-translational modification that regulates many aspects of cellular physiology, and dysregulation of pivotal phosphorylation events is often responsible for disease onset and progression. Clinical analysis on disease-relevant phosphoproteins, while quite challenging, provides unique information for precision medicine and targeted therapy. Among various approaches, mass spectrometry (MS)-centered characterization features discovery-driven, high-throughput and in-depth identification of phosphorylation events. This review highlights advances in sample preparation and instrument in MS-based phosphoproteomics and recent clinical applications. We emphasize the preeminent data-independent acquisition method in MS as one of the most promising future directions and biofluid-derived extracellular vesicles as an intriguing source of the phosphoproteome for liquid biopsy.

The first-in-class ERK inhibitor ulixertinib shows promising activity in mitogen-activated protein kinase (MAPK)-driven pediatric low-grade glioma models

BACKGROUND

Pediatric low-grade gliomas (pLGG) are the most common pediatric central nervous system tumors, with driving alterations typically occurring in the MAPK pathway. The ERK1/2 inhibitor ulixertinib (BVD-523) has shown promising responses in adult patients with mitogen-activated protein kinase (MAPK)-driven solid tumors.

METHODS

We investigated the antitumoral activity of ulixertinib monotherapy as well as in combination with MEK inhibitors (MEKi), BH3-mimetics, or chemotherapy in pLGG. Patient-derived pLGG models reflecting the two most common alterations in the disease, KIAA1549:BRAF-fusion and BRAFV600E mutation (DKFZ-BT66 and BT40, respectively) were used for in vitro and in vivo (zebrafish embryos and mice) efficacy testing.

RESULTS

Ulixertinib inhibited MAPK pathway activity in both models, and reduced cell viability in BT40 with clinically achievable concentrations in the low nanomolar range. Combination treatment of ulixertinib with MEKi or BH3-mimetics showed strong evidence of antiproliferative synergy in vitro. Ulixertinib showed on-target activity in all tested combinations. In vivo, sufficient penetrance of the drug into brain tumor tissue in concentrations above the in vitro IC50 and reduction of MAPK pathway activity was achieved. In a preclinical mouse trial, ulixertinib mono- and combined therapies slowed tumor growth and increased survival.

CONCLUSIONS

These data indicate a high clinical potential of ulixertinib for the treatment of pLGG and strongly support its first clinical evaluation in pLGG as single agent and in combination therapy in a currently planned international phase I/II umbrella trial.

AKT/mTOR signaling modulates resistance to endocrine therapy and CDK4/6 inhibition in metastatic breast cancers

Endocrine therapy (ET) in combination with CDK4/6 inhibition is routinely used as first-line treatment for HR+/HER2- metastatic breast cancer (MBC) patients. However, 30-40% of patients quickly develop disease progression. In this open-label multicenter clinical trial, we utilized a hypothesis-driven protein/phosphoprotein-based approach to identify predictive markers of response to ET plus CDK4/6 inhibition in pre-treatment tissue biopsies. Pathway-centered signaling profiles were generated from microdissected tumor epithelia and surrounding stroma/immune cells using the reverse phase protein microarray. Phosphorylation levels of the CDK4/6 downstream substrates Rb (S780) and FoxM1 (T600) were higher in patients with progressive disease (PD) compared to responders (p = 0.02). Systemic PI3K/AKT/mTOR activation in tumor epithelia and stroma/immune cells was detected in patients with PD. This activation was not explained by underpinning genomic alterations alone. As the number of FDA-approved targeted compounds increases, functional protein-based signaling analyses may become a critical component of response prediction and treatment selection for MBC patients.

Analysis of neuroendocrine clones in NSCLCs using an immuno-guided laser-capture microdissection-based approach

Clonal evolution and lineage plasticity are key contributors to tumor heterogeneity and response to treatment in cancer. However, capturing signal transduction events in coexisting clones remains challenging from a technical perspective. In this study, we developed and tested a signal-transduction-based workflow to isolate and profile coexisting clones within a complex cellular system like non-small cell lung cancers (NSCLCs). Cooccurring clones were isolated under immunohistochemical guidance using laser-capture microdissection, and cell signaling activation portraits were measured using the reverse-phase protein microarray. To increase the translational potential of this work and capture druggable vulnerabilities within different clones, we measured expression/activation of a panel of key drug targets and downstream substrates of FDA-approved or investigational agents. We isolated intermixed clones, including poorly represented ones (<5% of cells), within the tumor microecology and identified molecular characteristics uniquely attributable to cancer cells that undergo lineage plasticity and neuroendocrine transdifferentiation in NSCLCs.

The landscape of receptor-mediated precision cancer combination therapy via a single-cell perspective

Mining a large cohort of single-cell transcriptomics data, here we employ combinatorial optimization techniques to chart the landscape of optimal combination therapies in cancer. We assume that each individual therapy can target any one of 1269 genes encoding cell surface receptors, which may be targets of CAR-T, conjugated antibodies or coated nanoparticle therapies. We find that in most cancer types, personalized combinations composed of at most four targets are then sufficient for killing at least 80% of tumor cells while sparing at least 90% of nontumor cells in the tumor microenvironment. However, as more stringent and selective killing is required, the number of targets needed rises rapidly. Emerging individual targets include PTPRZ1 for brain and head and neck cancers and EGFR in multiple tumor types. In sum, this study provides a computational estimate of the identity and number of targets needed in combination to target cancers selectively and precisely.

Laser Capture Proteomics: spatial tissue molecular profiling from the bench to personalized medicine

INTRODUCTION

Laser Capture Microdissection (LCM) uses a laser to isolate, or capture, specific cells of interest in a complex heterogeneous tissue section, under direct microscopic visualization. Recently, there has been a surge of publications using LCM for tissue spatial molecular profiling relevant to a wide range of research topics.

AREAS COVERED

We summarize the many advances in tissue Laser Capture Proteomics (LCP) using mass spectrometry for discovery, and protein arrays for signal pathway network mapping. This review emphasizes: a) transition of LCM phosphoproteomics from the lab to the clinic for individualized cancer therapy, and b) the emerging frontier of LCM single cell molecular analysis combining proteomics with genomic, and transcriptomic analysis. The search strategy was based on the combination of MeSH terms with expert refinement.

EXPERT OPINION

LCM is complemented by a rich set of instruments, methodology protocols, and analytical A.I. (artificial intelligence) software for basic and translational research. Resolution is advancing to the tissue single cell level. A vision for the future evolution of LCM is presented. Emerging LCM technology is combining digital and AI guided remote imaging with automation, and telepathology, to a achieve multi-omic profiling that was not previously possible.

PD-L1 quantification across tumor types using the reverse phase protein microarray: implications for precision medicine

BACKGROUND

Anti-programmed cell death protein 1 and programmed cell death ligand 1 (PD-L1) agents are broadly used in first-line and second-line treatment across different tumor types. While immunohistochemistry-based assays are routinely used to assess PD-L1 expression, their clinical utility remains controversial due to the partial predictive value and lack of standardized cut-offs across antibody clones. Using a high throughput immunoassay, the reverse phase protein microarray (RPPA), coupled with a fluorescence-based detection system, this study compared the performance of six anti-PD-L1 antibody clones on 666 tumor samples.

METHODS

PD-L1 expression was measured using five antibody clones (22C3, 28-8, CAL10, E1L3N and SP142) and the therapeutic antibody atezolizumab on 222 lung, 71 ovarian, 52 prostate and 267 breast cancers, and 54 metastatic lesions. To capture clinically relevant variables, our cohort included frozen and formalin-fixed paraffin-embedded samples, surgical specimens and core needle biopsies. Pure tumor epithelia were isolated using laser capture microdissection from 602 samples. Correlation coefficients were calculated to assess concordance between antibody clones. For two independent cohorts of patients with lung cancer treated with nivolumab, RPPA-based PD-L1 measurements were examined along with response to treatment.

RESULTS

Median-center PD-L1 dynamic ranged from 0.01 to 39.37 across antibody clones. Correlation coefficients between the six antibody clones were heterogeneous (range: -0.48 to 0.95) and below 0.50 in 61% of the comparisons. In nivolumab-treated patients, RPPA-based measurement identified a subgroup of tumors, where low PD-L1 expression equated to lack of response.

CONCLUSIONS

Continuous RPPA-based measurements capture a broad dynamic range of PD-L1 expression in human specimens and heterogeneous concordance levels between antibody clones. This high throughput immunoassay can potentially identify subgroups of tumors in which low expression of PD-L1 equates to lack of response to treatment.

Next-Generation Sequencing-Directed Therapy in Patients with Metastatic Breast Cancer in Routine Clinical Practice

Next-generation sequencing (NGS) followed by matched therapy has opened up new therapeutic options to patients with metastatic breast cancer (mBC). Here we report our experience with this approach in everyday clinical practice. This retrospective study included 95 patients with mBC who were genotyped with the FoundationOne® (CDx) assay in a commercial molecular pathology laboratory. Genetic alterations were identified in all tumor specimens, and 83 patients (87.4%) had a median of 2 (range, 1-6) potentially actionable alterations. A multidisciplinary tumor board recommended genomically guided therapy to 63 patients, 30 of whom received such treatment. Everolimus (n = 15) and anti-human epidermal growth factor receptor 2 (HER2) therapy (n = 6) were most frequently administered. The ratio of progression-free survival (PFS) under NGS-based therapy to PFS under the last line of standard therapy prior to NGS was >1.3 in 13 (43.3%) patients, indicative of a clinical benefit to NGS-directed therapy. One-year overall survival rates were 22.7% (95% CI, 6.5-44.4) in 65 patients allocated to the standard therapy versus 62.9% (95% CI, 41.6-78.2) in 30 patients receiving the matched therapy. In conclusion, NGS-matched treatment improved the clinical outcomes in a subgroup of mBC patients.

Multi-omic molecular profiling guide's efficacious treatment selection in refractory metastatic breast cancer: a prospective phase II clinical trial

This prospective phase II clinical trial (Side Out 2) explored the clinical benefits of treatment selection informed by multi‐omic molecular profiling (MoMP) in refractory metastatic breast cancers (MBCs). Core needle biopsies were collected from 32 patients with MBC at trial enrollment. Patients had received an average of 3.94 previous lines of treatment in the metastatic setting before enrollment in this study. Samples underwent MoMP, including exome sequencing, RNA sequencing (RNA‐Seq), immunohistochemistry, and quantitative protein pathway activation mapping by Reverse Phase Protein Microarray (RPPA). Clinical benefit was assessed using the previously published growth modulation index (GMI) under the hypothesis that MoMP‐selected therapy would warrant further investigation for GMI ≥ 1.3 in ≥ 35% of the patients. Of the 32 patients enrolled, 29 received treatment based on their MoMP and 25 met the follow‐up criteria established by the trial protocol. Molecular information was delivered to the tumor board in a median time frame of 14 days (11–22 days), and targetable alterations for commercially available agents were found in 23/25 patients (92%). Of the 25 patients, 14 (56%) reached GMI ≥ 1.3. A high level of DNA topoisomerase I (TOPO1) led to the selection of irinotecan‐based treatments in 48% (12/25) of the patients. A pooled analysis suggested clinical benefit in patients with high TOPO1 expression receiving irinotecan‐based regimens (GMI ≥ 1.3 in 66.7% of cases). These results confirmed previous observations that MoMP increases the frequency of identifiable actionable alterations (92% of patients). The MoMP proposed allows the identification of biomarkers that are frequently expressed in MBCs and the evaluation of their role as predictors of response to commercially available agents. Lastly, this study confirmed the role of MoMP for informing treatment selection in refractory MBC patients: more than half of the enrolled patients reached a GMI ≥ 1.3 even after multiple lines of previous therapies for metastatic disease.

Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions

BACKGROUND

Targeted sequencing using oncopanels requires comprehensive assessments of accuracy and detection sensitivity to ensure analytical validity. By employing reference materials characterized by the U.S. Food and Drug Administration-led SEquence Quality Control project phase2 (SEQC2) effort, we perform a cross-platform multi-lab evaluation of eight Pan-Cancer panels to assess best practices for oncopanel sequencing.

RESULTS

All panels demonstrate high sensitivity across targeted high-confidence coding regions and variant types for the variants previously verified to have variant allele frequency (VAF) in the 5-20% range. Sensitivity is reduced by utilizing VAF thresholds due to inherent variability in VAF measurements. Enforcing a VAF threshold for reporting has a positive impact on reducing false positive calls. Importantly, the false positive rate is found to be significantly higher outside the high-confidence coding regions, resulting in lower reproducibility. Thus, region restriction and VAF thresholds lead to low relative technical variability in estimating promising biomarkers and tumor mutational burden.

CONCLUSION

This comprehensive study provides actionable guidelines for oncopanel sequencing and clear evidence that supports a simplified approach to assess the analytical performance of oncopanels. It will facilitate the rapid implementation, validation, and quality control of oncopanels in clinical use.

NGS-guided precision oncology in metastatic breast and gynecological cancer: first experiences at the CCC Munich LMU

Purpose

Comprehensive genomic profiling identifying actionable molecular alterations aims to enable personalized treatment for cancer patients. The purpose of this analysis was to retrospectively assess the impact of personalized recommendations made by a multidisciplinary tumor board (MTB) on the outcome of patients with breast or gynecological cancers, who had progressed under standard treatment. Here, first experiences of our Comprehensive Cancer Center Molecular Tumor Board are reported.

Methods

All patients were part of a prospective local registry. 95 patients diagnosed with metastatic breast cancer or gynecological malignancies underwent extended molecular profiling. From May 2017 through March 2019, the MTB reviewed all clinical cases considering tumor profile and evaluated molecular alterations regarding further diagnostic and therapeutic recommendations.

Results

95 patients with metastatic breast or gynecological cancers were discussed in the MTB (68% breast cancer, 20% ovarian cancer, 5% cervical cancer, 3% endometrial cancer and 4% others). Genes with highest mutation rate were PIK3CA and ERBB2. Overall, 34 patients (36%) received a biomarker-based targeted therapy recommendation. Therapeutic recommendations were implemented in nine cases; four patients experienced clinical benefit with a partial response or disease stabilization lasting over 4 months.

Conclusion

In the setting of a multidisciplinary molecular tumor board, a small but clinically meaningful group of breast and gynecological cancer patients benefits from comprehensive genomic profiling. Broad and successful implementation of precision medicine is complicated by patient referral at late stage disease and limited access to targeted agents and early clinical trials.

Trial registration number

284-10 (03.05.2018).

Integrating proteomics into precision oncology

DNA sequencing and RNA sequencing are increasingly applied in precision oncology, where molecular tumor boards evaluate the actionability of genetic events in individual tumors to guide targeted treatment. To work toward an additional level of patient characterization, we assessed the abundance and activity of 27 proteins in 134 patients whose tumors had previously undergone whole-exome and RNA sequencing within the Molecularly Aided Stratification for Tumor Eradication Research (MASTER) program of National Center for Tumor Diseases, Heidelberg. Proteomic and phosphoproteomic targets were selected to reflect the most relevant therapeutic baskets in MASTER. Among six different therapeutic baskets, the proteomic data supported treatment recommendations that were based on DNA and RNA analyses in 10% to 57% and frequently suggested alternative treatment options. In several cases, protein activities explained the patients' clinical course and provided potential explanations for treatment failure. Our study indicates that the integrative analysis of DNA, RNA and protein data may refine therapeutic stratification of individual patients and, thus, holds potential to increase the success rate of precision cancer therapy. Prospective validation studies are needed to advance the integration of proteomic analysis into precision oncology.

High expression of FUSE binding protein 1 in breast cancer stimulates cell proliferation and diminishes drug sensitivity

Breast cancer is the most common malignant tumor affecting women worldwide and is divided into the following subtypes: Luminal A, Luminal B, HER-2 overexpression and triple-negative breast cancer (TNBC). TNBC accounts for approximately 15-20% of all breast cancer cases. Due to the characteristics of low differentiation, the likelyhood of recurrence and metastasis, strong invasiveness and the lack of hormone receptors and human epidermal growth factor receptor 2 (HER2), patients with TNBC cannot benefit from endocrine therapy or other available targeted agents. Chemotherapy is one of the main treatments for patients with TNBC, and cisplatin is one of the most commonly used and effective drugs. The human far upstream element binding protein 1 (FBP1) is a potent pro-proliferative and anti-apoptotic oncoprotein, which is overexpressed in numerous tumor types. The present study demonstrated that FBP1 and its target, c-Myc, were more highly expressed in breast cancer tissues compared with para-carcinoma tissues, and the FBP1 and c-Myc levels are decreased by cisplatin treatment. The knockdown of FBP1 in TNBC cells decreased cell proliferation by arresting the cell cycle at the G2 phase. The knockdown of FBP1 decreased the expression of G2 phase-associateed protein cyclin A2, whereas it increased that of cyclin B1 and p-CDC2. Furthermore, the knockdown of FBP1 decreased cell migration and metastasis by downregulating matrix metalloproteinase 2 expression, and enhanced the sensitivity of TNBC cells to cisplatin by inducing apoptosis. These results thus suggest that FBP1 is a potential novel biological marker for the diagnosis and treatment of TNBC.

Support of a molecular tumour board by an evidence-based decision management system for precision oncology

BACKGROUND

Reliable and reproducible interpretation of molecular aberrations constitutes a bottleneck of precision medicine. Evidence-based decision management systems may improve rational therapy recommendations. To cope with an increasing amount of complex molecular data in the clinical care of patients with cancer, we established a workflow for the interpretation of molecular analyses.

METHODS

A specialized physician screened results from molecular analyses for potential biomarkers, irrespective of the diagnostic modality. Best available evidence was retrieved and categorized through establishment of an in-house database and interrogation of publicly available databases. Annotated biomarkers were ranked using predefined evidence levels and subsequently discussed at a molecular tumour board (MTB), which generated treatment recommendations. Subsequent translation into patient treatment and clinical outcomes were followed up.

RESULTS

One hundred patients were discussed in the MTB between January 2016 and May 2017. Molecular data were obtained for 70 of 100 patients (50 whole exome/RNA sequencing, 18 panel sequencing, 2 immunohistochemistry (IHC)/microsatellite instability analysis). The MTB generated a median of two treatment recommendations each for 63 patients. Thirty-nine patients were treated: 6 partial responses and 12 stable diseases were achieved as best responses. Genetic counselling for germline events was recommended for seven patients.

CONCLUSION

The development of an evidence-based workflow allowed for the clinical interpretation of complex molecular data and facilitated the translation of personalized treatment strategies into routine clinical care. The high number of treatment recommendations in patients with comprehensive genomic data and promising responses in patients treated with combination therapy warrant larger clinical studies.

Cost-comparison analysis of a multiplatform tumour profiling service to guide advanced cancer treatment

Background

Tumor profiling is increasingly used in advanced cancer patients to define treatment options, especially in refractory cases where no standard treatment is available. Caris Molecular Intelligence (CMI) is a multiplatform tumor profiling service that is comprehensive of next-generation sequencing (NGS) of DNA and RNA, immunohistochemistry (IHC) and in situ hybridisation (FISH). The aim of this study is to compare costs of CMI-guided treatment with prior or planned treatment options in correlation with outcome results.

Methods

Retrospective data from five clinical trials were collected to define the treatment decision prior to the receipt of the CMI report (n = 137 patients). A systematic review of treatment data from 11 clinical studies of CMI (n = 385 patients) allowed a comparison of planned vs actual (n = 137) and prior vs actual (n = 229) treatment costs.

Results

Treatment plan was changed in 88% of CMI-profiled cases. The actual CMI guided treatment cost per cycle was £995 in 385 treated patients. Planned treatment costs were comparable to actual treatment costs (£979 vs £945; p = 0.7123) and prior treatment costs were not significantly different to profiling-guided treatments (£892 vs £850; p = 0.631).

Conclusions

Caris Molecular Intelligence guided treatment cost per cycle was in the range of prior or planned treatment cost/cycle. Due to beneficial overall survival the additional cost of performing CMI's multiplatform testing to the treatment costs seems to be cost-effective.

Everolimus-containing therapy vs conventional therapy in the treatment of refractory breast cancer patients with PI3K/AKT/mTOR mutations: A retrospective study

Background

Previous case reports have shown the promising antitumor activity of everolimus in solid tumors containing molecular aberrations in PI3K/ATK/mTOR pathway, however, whether it is effective in patients with breast cancer remains unknown. Therefore, we conducted this retrospective cohort study to compare the efficacy of molecularly matched targeted therapy with everolimus to conventional therapy in refractory breast cancer patients harboring PI3K/ATK/mTOR pathway activating mutations.

Methods

Refractory metastatic breast cancer patients who have received molecular screening using next‐generation sequencing (NGS) between September 8, 2015 and October 30, 2017 in two sites were screened for this study. The primary outcome was progression‐free survival (PFS). The secondary outcomes were overall response rate (ORR), disease control rate (DCR), and safety profile.

Results

A total of 78 patients were screened for analysis, amongst all, 52 (66.7%) had at least one gene mutation in PI3K/AKT/mTOR pathway. The most common mutation fell in PIK3CA (76.9%, 40/52) with a mutational prevalence of 51.3%. Of the 32 patients who were eligible for efficacy analysis, patients in the everolimus group (n = 19) exhibited shorter PFS than those in the conventional group (n = 13) (median, 1.9 vs 6.1 months; HR, 3.6; 95% CI, 1.48‐8.81; P = .0005). ORR was 15.4% (2/13) in the everolimus group and 23.1% (3/13) in the conventional group (P = 1.000), and DCR was 30.8% (4/13) and 100% (13/13) for each group, respectively (P = .000). The incidence of grade 3‐5 adverse events was relatively higher in the conventional group (38.5%, 5/13) than that in the everolimus group (26.3%, 5/19).

Conclusions

Our findings suggested that everolimus might not be effective for cancer patients harboring mutations in PI3K/ATK/mTOR pathway and physicians should be cautious about its off‐label use in clinical practice.

Genomic heterogeneity and efficacy of PI3K pathway inhibitors in patients with gynaecological cancer

Objectives

Aberrant PI3K/AKT/mTOR activation is common in gynaecological malignancies. However, predictive biomarkers of response to PI3K pathway inhibitors (PAMi) have yet to be identified.

Methods

We analysed the outcomes of patients with advanced gynaecological cancer with available genomic data, treated with PAMi as single agents or in combination in phase I clinical trials. Clinical relevance of the PIK3CA mutant allele fraction (MAF) was investigated. MAF of each variant was normalised for tumour purity in the sample (adjMAFs) to infer clonality of PIK3CA mutations, defined as clonal (≥0.4) or subclonal (<0.4).

Results

A total of 50 patients with gynaecological cancer (24 ovarian; 15 endometrial; 11 cervical) with available targeted mutation profiling were selected. PAMi therapy was matched to PIK3CA/PTEN mutation in 30 patients (60%). The overall response rate, median time to progression (mTTP) and clinical benefit rate (CBR) of the entire population were 10% (N=5), 3.57 months (2.57-4.4) and 40% (N=18), respectively. Genotype-matched therapy did not lead to a favourable CBR (OR 0.91, p=1 (0.2-3.7)) or mTTP (3.57 months (2.6-4.4) vs 3.73 months (1.9-13.2); HR 1.41; p=0.29). We did not detect differences in mTTP according to therapy or PIK3CA codon mutation (HR 1.71, p=0.24). Overall, 41% of patients had a TTP ratio (TTP PAMi/TTP on immediately prior or subsequent palliative chemotherapy) ≥1.3, without statistically significant differences according to tumour type (p=0.39), molecular alteration status (p=0.13) or therapy (p=0.54). In univariate analysis, genotype-matched therapy in patients with PIK3CA clonal events was associated with improved mTTP (HR 3.6; p=0.03).

Conclusions

Our study demonstrates that patients with advanced gynaecological cancer, refractory to standard therapies, achieved meaningful clinical benefit from PAMi. The impact of PI3KCA clonality on response to selected PAMi in patients with gynaecological cancer deserves further investigation.

Genomic heterogeneity and efficacy of PI3K pathway inhibitors in patients with gynaecological cancer

OBJECTIVES

Aberrant PI3K/AKT/mTOR activation is common in gynaecological malignancies. However, predictive biomarkers of response to PI3K pathway inhibitors (PAMi) have yet to be identified.

METHODS

We analysed the outcomes of patients with advanced gynaecological cancer with available genomic data, treated with PAMi as single agents or in combination in phase I clinical trials. Clinical relevance of the PIK3CA mutant allele fraction (MAF) was investigated. MAF of each variant was normalised for tumour purity in the sample (adjMAFs) to infer clonality of PIK3CA mutations, defined as clonal (≥0.4) or subclonal (<0.4).

RESULTS

A total of 50 patients with gynaecological cancer (24 ovarian; 15 endometrial; 11 cervical) with available targeted mutation profiling were selected. PAMi therapy was matched to PIK3CA/PTEN mutation in 30 patients (60%). The overall response rate, median time to progression (mTTP) and clinical benefit rate (CBR) of the entire population were 10% (N=5), 3.57 months (2.57-4.4) and 40% (N=18), respectively. Genotype-matched therapy did not lead to a favourable CBR (OR 0.91, p=1 (0.2-3.7)) or mTTP (3.57 months (2.6-4.4) vs 3.73 months (1.9-13.2); HR 1.41; p=0.29). We did not detect differences in mTTP according to therapy or PIK3CA codon mutation (HR 1.71, p=0.24). Overall, 41% of patients had a TTP ratio (TTP PAMi/TTP on immediately prior or subsequent palliative chemotherapy) ≥1.3, without statistically significant differences according to tumour type (p=0.39), molecular alteration status (p=0.13) or therapy (p=0.54). In univariate analysis, genotype-matched therapy in patients with PIK3CA clonal events was associated with improved mTTP (HR 3.6; p=0.03).

CONCLUSIONS

Our study demonstrates that patients with advanced gynaecological cancer, refractory to standard therapies, achieved meaningful clinical benefit from PAMi. The impact of PI3KCA clonality on response to selected PAMi in patients with gynaecological cancer deserves further investigation.

Treatment According to a Comprehensive Molecular Profiling Can Lead to a Better Outcome in Heavily Pretreated Patients With Metastatic Cancer: Data of a Pooled Analysis

PURPOSE

Improvements in systemic treatment have led to a prolongation of survival and quality of life in patients with metastatic tumors in recent years. However, despite this improved standard of care, it is expected that the progression-free survival (PFS) for patients with refractory cancers will continue to decline over subsequent therapy lines. In those patients, studies and meta-analyses showed that treatment based on multiplatform molecular profiling (MMP) of tumor tissue may derive a clinical benefit. The aim of this study was to analyze if molecular-based therapy may prolong PFS compared with the PFS of the immediately prior therapy.

METHODS

We pooled clinical data of 140 patients treated within 3 recently conducted pilot studies and included an additional 21 patients who were treated within the ongoing ONCO-T-PROFILE program. The PFS of the molecular-based treatment was compared with the PFS of the previous therapy using Kaplan-Meier curves.

RESULTS

In heavily pretreated cancer patients, the PFS could be significantly improved using molecular-based treatment options (120.0 vs. 89.5 days). More than 50% of patients showed a clinical benefit from MMP-guided therapy as defined by a PFS ratio of 1.3 or greater.

CONCLUSIONS

We conclude that pretreated cancer patients can benefit from incorporation of molecular profiling, as demonstrated by not only an increase of the PFS ratio but also PFS. Further randomized trials in specific tumor subtypes may help establish specific patient populations who might benefit most from MMP guidance.

Genomic heterogeneity and efficacy of PI3K pathway inhibitors in patients with gynaecological cancer

OBJECTIVES

Aberrant PI3K/AKT/mTOR activation is common in gynaecological malignancies. However, predictive biomarkers of response to PI3K pathway inhibitors (PAMi) have yet to be identified.

METHODS

We analysed the outcomes of patients with advanced gynaecological cancer with available genomic data, treated with PAMi as single agents or in combination in phase I clinical trials. Clinical relevance of the PIK3CA mutant allele fraction (MAF) was investigated. MAF of each variant was normalised for tumour purity in the sample (adjMAFs) to infer clonality of PIK3CA mutations, defined as clonal (≥0.4) or subclonal (<0.4).

RESULTS

A total of 50 patients with gynaecological cancer (24 ovarian; 15 endometrial; 11 cervical) with available targeted mutation profiling were selected. PAMi therapy was matched to PIK3CA/PTEN mutation in 30 patients (60%). The overall response rate, median time to progression (mTTP) and clinical benefit rate (CBR) of the entire population were 10% (N=5), 3.57 months (2.57-4.4) and 40% (N=18), respectively. Genotype-matched therapy did not lead to a favourable CBR (OR 0.91, p=1 (0.2-3.7)) or mTTP (3.57 months (2.6-4.4) vs 3.73 months (1.9-13.2); HR 1.41; p=0.29). We did not detect differences in mTTP according to therapy or PIK3CA codon mutation (HR 1.71, p=0.24). Overall, 41% of patients had a TTP ratio (TTP PAMi/TTP on immediately prior or subsequent palliative chemotherapy) ≥1.3, without statistically significant differences according to tumour type (p=0.39), molecular alteration status (p=0.13) or therapy (p=0.54). In univariate analysis, genotype-matched therapy in patients with PIK3CA clonal events was associated with improved mTTP (HR 3.6; p=0.03).

CONCLUSIONS

Our study demonstrates that patients with advanced gynaecological cancer, refractory to standard therapies, achieved meaningful clinical benefit from PAMi. The impact of PI3KCA clonality on response to selected PAMi in patients with gynaecological cancer deserves further investigation.

Impact of molecular testing in clinical practice in gynecologic cancers

Background

With the growing understanding of the molecular and genetic profiles of cancers, targeted treatments are increasingly utilized in personalized cancer care. The objective of this study was to determine how these advances have translated into practice by examining how often molecular profiling of gynecological tumors led to treatment changes.

Methods

We identified women with gynecological cancers at our institution who had molecular tumor testing performed from November 2014 to June 2017. Clinicopathologic data were extracted from medical records. We determined (a) if molecular profiling identified actionable targets for which therapy is available, and (b) whether the patient's treatment course changed as a result of molecular profiling. Chi‐square, Wilcoxon rank‐sum, and Fisher's exact tests were used with a P < 0.05 considered statistically significant.

Results

We identified 152 patients with gynecologic cancers who underwent molecular profiling. Of the 152 patients, 116 (76.3%) had actionable mutations identified, with 41 (35.3%) patients having a treatment change. Stratified by cancer type, molecular profiling most frequently identified an actionable target in patients with endometrial cancer (73.6%). Changes in treatment occurred most frequently in patients with endometrial cancer, 22 (56.4%), and ovarian cancers, 16 (39%), as compared to patients with cervical and vulvar cancer (P = 0.02). Of those patients who received a change in treatment, 39 patients (95.1%) received an FDA‐approved therapeutic agent, while two patients (4.8%) were enrolled in a clinical trial.

Conclusion

Molecular profiling in gynecologic cancers often identified at least one actionable mutation; however, only in a minority of these cases was the course of treatment changed. Further studies are needed to elucidate optimal timing for testing to best utilize actionable information.

Human Microbiota and Personalized Cancer Treatments: Role of Commensal Microbes in Treatment Outcomes for Cancer Patients

The human gut microbiota consists of about 3.8 × 10¹³ microorganisms that play an essential role in health, metabolism, and immunomodulation. These gut microbes alter therapeutic response and toxicity to cancer therapies including cytotoxic chemotherapy, radiation therapy, kinase inhibitors, and immunotherapy agents. The gut microbiota generates short-chain fatty acids that are significant regulators of histone post-translational modifications that fundamentally regulate gene expression, linking the microbiota to cellular metabolism and transcriptional regulation. The short-chain fatty acids not only act locally but can be taken up in the blood stream to inhibit the activity of histone deacetylases, regulate gene expression in distant organs as well as the effector function of CD8+ T cells. Cancer and the treatments for it negatively impact the microbiome often resulting in dysbiosis. This can diminish a patient's response to treatment as well as increase systemic toxicities from these therapies. In addition to the gut microbiota, microbes have been detected in tumors that can modulate chemotherapeutic drug response and can result in immune suppression. The gut microbiota and tumor-associated bacteria may be a significant contributor to the interindividual differences and heterogeneous responses to cancer therapies and drug tolerability and strategies that support and/or manipulate the microbiota to improve therapeutic outcome is an emerging area for personalized cancer treatment.

Update on Precision Medicine in Breast Cancer

Precision medicine approaches have found applications in the treatment of several tumor types and have led to rapid advancement in the number of available therapies for some difficult-to-treat diseases. In comparison to tumors like EGFR-mutated lung cancer, and BRAF-mutated melanoma for example, precision medicine in breast cancer is still in its infancy despite the much earlier identification of targets like ER and HER2. Though significant progress has been made in new therapies for hormone-receptor-positive and HER2-positive breast cancers, identification of molecular heterogeneity and lack of other valid reproducible targets in triple-negative breast cancer remain a challenge. In this chapter, we outline the recent advances in technology and targeted treatments for breast cancer, the remaining challenges and ongoing efforts to address these to make precision medicine a reality for all breast cancer patients.

RPPA: Origins, Transition to a Validated Clinical Research Tool, and Next Generations of the Technology

RPPA technology has graduated from a research tool to an essential component of clinical drug discovery research and personalized medicine. Next generations of RPPA technology will be a single clinical instrument that integrates all the steps of the workflow.

Determining personalized treatment by gene expression profiling in metastatic breast carcinoma patients: a pilot study

PURPOSE

The present study evaluates the massive study of gene expression in metastatic breast carcinoma (MBC) patients using microarray gene expression profiling (MAGE) complemented with conventional sequencing, immunohistochemistry (IHC) and fluorescent "in situ" hybridization (FISH), seeking to optimize the treatment in a subset of heavily pretreated patients and with limited life expectancy.

PATIENTS, MATERIAL AND METHODS

MBC patients in hormone therapy progression with survival expectancy of at least 3 months (m) have been included. The MAGE contains gene probes representing genes known to potentially interact with available drugs as cited in the literature.

RESULTS

Thirty-nine procedures were performed from October 2010 to April 2016. Within the 30 evaluable procedures, considering all hormonal manipulations as a single line, the patients had received a median of 4 treatment lines prior to MAGE (range 1-7). Progression was observed in 6 cases, stable disease (SD) in 7 cases and partial response (PR) in 16 cases, which implies a clinical benefit rate (SD + PR) of 76%. Actuarial median progression-free survival (PFS) was 6 m (95% CI 2.5-9.5) in patients with clinical benefit. The median overall survival (OS) for the entire series was 11 m (95% CI 2.2-19.8).

CONCLUSION

Data presented here indicate that the use of MAGE provides relevant information to establish personalized treatment in frail patients with limited life expectancy in which therapeutic futility is a particularly difficult burden to assume.

Protein drug target activation homogeneity in the face of intra-tumor heterogeneity: implications for precision medicine

Introduction: Recent studies indicated tumors may be comprised of heterogeneous molecular subtypes and incongruent molecular portraits may emerge if different areas of the tumor are sampled. This study explored the impact of intra-tumoral heterogeneity in terms of activation/phosphorylation of FDA approved drug targets and downstream kinase substrates.

Material and methods: Two independent sets of liver metastases from colorectal cancer were used to evaluate protein kinase-driven signaling networks within different areas using laser capture microdissection and reverse phase protein array.

Results: Unsupervised hierarchical clustering analysis indicated that the signaling architecture and activation of the MAPK and AKT-mTOR pathways were consistently maintained within different regions of the same biopsy. Intra-patient variability of the MAPK and AKT-mTOR pathway were <1.06 fold change, while inter-patients variability reached fold change values of 5.01.

Conclusions: Protein pathway activation mapping of enriched tumor cells obtained from different regions of the same tumor indicated consistency and robustness independent of the region sampled. This suggests a dominant protein pathway network may be activated in a high percentage of the tumor cell population. Given the genomic intra-tumoral variability, our data suggest that protein/phosphoprotein signaling measurements should be integrated with genomic analysis for precision medicine based analysis.

Change in Topoisomerase 1-Positive Circulating Tumor Cells Affects Overall Survival in Patients with Advanced Breast Cancer after Treatment with Etirinotecan Pegol

Purpose: Preplanned exploratory analyses were performed to identify biomarkers in circulating tumor cells (CTC) predictive of response to the topoisomerase 1 inhibitor etirinotecan pegol (EP).Experimental Design: The BEACON trial treated patients with metastatic breast cancer (MBC) with EP or treatment of physician's choice (TPC). Blood from 656 of 852 patients (77%) was processed with ApoStream to enrich for CTCs. A multiplex immunofluorescence assay measured expression of candidate response biomarkers [topoisomerase 1 (Top1), topoisomerase 2 (Top2), Ki67, RAD51, ABCG2, γH2AX, and terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL)] in CTCs. Patients were classified as Top1 low (Top1Lo) or Top1 high (Top1Hi) based on median CTC Top1 expression. Correlation of CTC biomarker expression at baseline, cycle 2 day 1 (C2D1), and cycle 4 day 1 with overall survival (OS) was investigated using Cox regression and Kaplan-Meier analyses.Results: Overall, 98% of samples were successfully processed, of which 97% had detectable CTCs (median, 47-63 CTCs/mL; range, 0-2,020 CTCs/mL). Top1, Top2, and TUNEL expression was detected in 52% to 90% of samples; no significant associations with OS were observed in pretreatment samples for either group. EP-treated patients with low C2D1Top1⁺ CTCs had improved OS compared with those with higher positivity (14.1 months vs. 11.0 months, respectively; HR, 0.7; P = 0.02); this difference was not seen in TPC-treated patients (HR, 1.12; P = 0.48). Patients whose CTCs decreased from Top1Hi to Top1Lo at C2D1 had the greatest OS benefit from EP (HR, 0.57; P = 0.01).Conclusions: CTC Top1 expression following EP treatment may identify patients with MBC most likely to have an OS benefit. Clin Cancer Res; 24(14); 3348-57. ©2018 AACR.

Dual-Color, Multiplex Analysis of Protein Microarrays for Precision Medicine

Generating molecular information in a clinically relevant time frame is the first hurdle to truly integrating precision medicine in health care. Reverse phase protein microarrays are being utilized in clinical trials for quantifying posttranslationally modified signal transduction proteins and cellular signaling pathways, allowing direct comparison of the activation state of proteins from multiple specimens, or individual patient specimens, within the same array. This technology provides diagnostic and therapeutic information critical to precision medicine. To enhance accessibility of this technology, two hurdles must be overcome: data normalization and data acquisition. Herein we describe an unamplified, dual-color signal detection methodology for reverse phase protein microarrays that allows multiplex, within spot data normalization, reduces data acquisition time, simplifies automated spot detection, and provides a stable signal output. This method utilizes Quantum Nanocrystal fluorophore labels (Qdot) substituted for organic fluorophores coupled with an imager (ArrayCAM) that captures images of the microarray rather than sequentially scanning the array. Streamlining and standardizing the data analysis steps with ArrayCAM high-resolution, dual mode chromogenic/fluorescent array imaging overcomes the data acquisition hurdle. The spot location and analysis algorithm provides certain parameter settings that can be tailored to the particular microarray type (fluorescent vs. colorimetric), resulting in greater than 99 % spot location sensitivity. The described method demonstrates equivalent sensitivity for a non-amplified Qdot immunoassay when using automated vs. manual immunostaining procedures.

A phase 2 trial of personalized cytotoxic therapy based on tumor immunohistochemistry in previously treated metastatic pancreatic cancer patients

Background

The choice of a regimen in metastatic pancreatic cancer patients following progression on 1st line therapy is empiric and outcomes are unsatisfactory. This phase II study was performed to evaluate the efficacy of therapy selected by immunohistochemistry (IHC) in these patients following progression after one or more therapies.

Methods

Eligible patients underwent a percutaneous biopsy of a metastatic lesion and treatment selection was determined by IHC. The study required 35 evaluable patients (power of 86%) for detecting a true 1-year survival rate of >20%.

Results

A tumor biopsy was performed in 48 of 49 accrued patients. Study therapy was not given (n=13) either due to insufficient tumor on biopsy (n=8) or due to worsening cancer related symptoms after biopsy (n=5). The demographics of evaluable patients (n=35) are male/female (59%/41%), with age range 34-78 years (median 63 years). Patients had 1-6 prior regimens (median of 2). The most common IHC targets were topoisomerase 1 or 2, thymidylate synthase, excision repair cross-complementation group 1 protein (ERCC1), and osteonectin secreted protein acidic and rich in cysteine (SPARC). Commercially available treatment regimens prescribed included FOLFIRI, FOLFOX, irinotecan, and doxorubicin. The response (RECIST) was 9%, the median survival was 5.6 months (94% CI, 3.8-8.2), and the 1-year survival was 20% (95% CI, 7-33%).

Conclusions

In all patients, IHC assays resulted in identification of at least two targets for therapy and a non-cross resistant regimen could be prescribed for therapy with evidence of some benefit. An IHC based treatment strategy is feasible and needs validation in larger studies.

Multi-platform molecular profiling of a large cohort of glioblastomas reveals potential therapeutic strategies

Glioblastomas (GBM) are the most aggressive and prevalent form of gliomas with abysmal prognosis and limited treatment options. We analyzed clinically relevant molecular aberrations suggestive of response to therapies in 1035 GBM tumors. Our analysis revealed mutations in 39 genes of 48 tested. IHC revealed expression of PD-L1 in 19% and PD-1 in 46%. MGMT-methylation was seen in 43%, EGFRvIII in 19% and 1p19q co-deletion in 2%. TP53 mutation was associated with concurrent mutations, while IDH1 mutation was associated with MGMT-methylation and TP53 mutation and was mutually exclusive of EGFRvIII mutation. Distinct biomarker profiles were seen in GBM compared with WHO grade III astrocytoma, suggesting different biology and potentially different treatment approaches. Analysis of 17 metachronous paired tumors showed frequent biomarker changes, including MGMT-methylation and EGFR aberrations, indicating the need for a re-biopsy for tumor profiling to direct subsequent therapy. MGMT-methylation, PR and TOPO1 appeared as significant prognostic markers in sub-cohorts of GBM defined by age. The current study represents the largest biomarker study on clinical GBM tumors using multiple technologies to detect gene mutation, amplification, protein expression and promoter methylation. These data will inform planning for future personalized biomarker-based clinical trials and identifying effective treatments based on tumor biomarkers.

Impact of molecular profiling on overall survival of patients with advanced ovarian cancer

OBJECTIVE

Patients with recurrent epithelial ovarian cancer (EOC) have limited treatment options. Studies have reported that biomarker profiling may help predict patient response to available treatments. This study sought to determine the value of biomarker profiling in recurrent EOC.

RESULTS

Patients in the Matched cohort had a median OS of 36 months compared to 27 months for patients in the Unmatched cohort (HR 0.62, 95% CI 0.41-0.96; p < 0.03). Individual biomarkers were analyzed, with TUBB3, and PGP prognostic for survival. Biomarker analysis also identified a molecular subtype (positive for at least two of the following markers: ERCC1, RRM1, TUBB3, PGP) with particularly poor overall survival.

METHODS

224 patients from a commercial registry (NCT02678754) with stage IIIC/IV EOC at diagnosis, or restaged to IIIC/IV EOC at the time of molecular profiling, were retrospectively divided into two cohorts based on whether or not the drugs they received matched their profile recommendations. The Matched cohort received no drugs predicted to be lack-of-benefit while the Unmatched cohort received at least one drug predicted to be lack-of-benefit. Profile biomarker/drug associations were based on multiple test platforms including immunohistochemistry, fluorescent in situ hybridization and DNA sequencing.

CONCLUSIONS

This report demonstrates the ability of multi-platform molecular profiling to identify EOC patients at risk of inferior survival. It also suggests a potential beneficial role of avoidance of lack-of-benefit therapies which, when administered, resulted in decreased survival relative to patients who received only therapies predicted to be of benefit.

Reverse phase protein array (RPPA) combined with computational analysis to unravel relevant prognostic factors in non- small cell lung cancer (NSCLC): a pilot study

In this work high throughput technology and computational analysis were used to study two stage IV lung adenocarcinoma patients treated with standard chemotherapy with markedly different survival (128 months vs 6 months, respectively) and whose tumor samples exhibit a dissimilar protein activation pattern of the signal transduction. Tumor samples of the two patients were subjected to Reverse Phase Protein Microarray (RPPA) analysis to explore the expression/activation levels of 51 signaling proteins. We selected the most divergent proteins based on the ratio of their RPPA values in the two patients with short (s-OS) and long (l-OS) overall survival (OS) and tested them against a EGFR-IGF1R mathematical model. The model with RPPA data showed that the activation levels of 19 proteins were different in the two patients. The four proteins that most distinguished the two patients were BADS155/136 and c-KITY703/719 having a higher activation level in the patient with short survival and p70S6S371/T389 and b-RAFS445 that had a lower activation level in the s-OS patient. The final model describes the interactions between the MAPK and PI3K-mTOR pathways, including 21 nodes. According to our model mTOR and ERK activation levels were predicted to be lower in the s-OS patient than the l-OS patient, while the AMPK activation level was higher in the s-OS patient. Moreover, KRAS activation was predicted to be higher in the l-OS KRAS-mutated patient. In accordance with their different biological properties, the Moment Independent Robustness Indicator in s-OS and l-OS predicted the interaction of MAPK and mTOR and the crosstalk AKT with p90RSK as candidates to be prognostic factors and drug targets.

Knockdown of FUSE binding protein 1 enhances the sensitivity of epithelial ovarian cancer cells to carboplatin

Epithelial ovarian cancer (EOC) affects almost 25,000 women annually and is the fifth most common malignancy in women in North America. A combination of surgery and cytotoxic chemotherapy may produce a favorable clinical response. The platinum-paclitaxel combination regimen is the chemotherapy gold-standard for advanced ovarian cancer, and carboplatin is one of the agents in this combination therapy. However, the majority of patients eventually experience a relapse due to the development of platinum resistance. FUSE binding protein 1 (FBP1) has been identified as an anti-apoptotic and pro-proliferative oncoprotein that is overexpressed in hepatocellular carcinoma. Its high expression is also associated with carboplatin resistance. In the present study, it was identified that the expression of FBP1 was significantly higher in EOC tissues than in normal epithelial ovarian or in epithelial ovarian adenoma tissue. FBP1 expression was significantly correlated with the grade of epithelial ovarian cancer. Carboplatin inhibited the expression of FBP1 in epithelial ovarian cancer cells and the knockdown of FBP1 enhanced the inhibition of cell viability and migration by carboplatin. In addition to FBP1, carboplatin also inhibited the expression of β-catenin and matrix metalloproteinase (MMP)-9. Furthermore, the expression of β-catenin and MMP-9 were lower in FBP1 knockdown cells compared with control EOC cells. FBP1 may thus serve a role in the regulation of the expression of β-catenin and MMP-9; the inhibition of β-catenin and MMP-9 by carboplatin may be mediated through the inhibition of FBP1. The inhibition of FBP1 expression by carboplatin may be a mechanism in the treatment of EOC by carboplatin.

Kinase-driven metabolic signalling as a predictor of response to carboplatin-paclitaxel adjuvant treatment in advanced ovarian cancers

BACKGROUND

The biological mechanisms underlying early- and advanced-stage epithelial ovarian cancers (EOCs) are still poorly understood. This study explored kinase-driven metabolic signalling in early and advanced EOCs, and its role in tumour progression and response to carboplatin-paclitaxel treatment.

METHODS

Tumour epithelia were isolated from two independent sets of primary EOC (n=72 and 30 for the discovery and the validation sets, respectively) via laser capture microdissection. Reverse phase protein microarrays were used to broadly profile the kinase-driven metabolic signalling of EOC with particular emphasis on the LBK1-AMPK and AKT-mTOR axes. Signalling activation was compared between early and advanced lesions, and carboplatin-paclitaxel-sensitive and -resistant tumours.

RESULTS

Advanced EOCs were characterised by a heterogeneous kinase-driven metabolic signature and decreased phosphorylation of the AMPK-AKT-mTOR axis compared to early EOC (P<0.05 for AMPKα T172, AMPKα1 S485, AMPKβ1 S108, AKT S473 and T308, mTOR S2448, p70S6 S371, 4EBP1 S65, GSK-3 α/β S21/9, FOXO1 T24/FOXO3 T32, and FOXO1 S256). Advanced tumours with low relative activation of the metabolic signature and increased FOXO1 T24/FOXO3 T32 phosphorylation (P=0.041) were associated with carboplatin-paclitaxel resistance.

CONCLUSIONS

If validated in a larger cohort of patients, the decreased AMPK-AKT-mTOR activation and phosphorylation of FOXO1 T24/FOXO3 T32 may help identify carboplatin-paclitaxel-resistant EOC patients.

Signaling pathway profiling using reverse-phase protein array and its clinical applications

INTRODUCTION

Increased accessibility to next-generation sequencing within the last decade has led to a paradigm shift in cancer treatment from one-size-fits-all medicine to precision medicine providing therapeutic strategies tailored to the requirements of individual patients. However, the effect of even the most successful agent yet tested is only transient, and durable efficacy has yet to be achieved. Genome- and transcriptome-based approaches cannot fully predict the diversity of protein expression patterns or post-translational modifications that directly contribute to cancer pathogenesis and physiology. This underscores the need for concordant proteomic analysis in the next stage of precision medicine. Areas covered: This review begins with an overview of the recent advances and trends in precision medicine that currently rely on genomics, and highlights the utility of antibody-based reverse-phase protein array (RPPA) technology as a proteomic tool in this context. Expert commentary: RPPA is well suited for pharmacodynamics analysis in view of its ability to precisely map signaling status using limited amounts of clinical samples. In addition, the cost-effectiveness and rapid turn-around time of the RPPA platform offer a substantial advantage over existing molecular profiling technologies in clinical settings.

Enrichment of PI3K-AKT-mTOR Pathway Activation in Hepatic Metastases from Breast Cancer

Purpose: Little is known about the molecular signatures associated with specific metastatic sites in breast cancer. Using comprehensive multi-omic molecular profiling, we assessed whether alterations or activation of the PI3K-AKT-mTOR pathway is associated with specific sites of breast cancer metastasis.Experimental Design: Next-generation sequencing-based whole-exome sequencing was coupled with reverse-phase protein microarray (RPPA) functional signaling network analysis to explore the PI3K-AKT-mTOR axis in 32 pretreated breast cancer metastases. RPPA-based signaling data were further validated in an independent cohort of 154 metastatic lesions from breast cancer and 101 unmatched primary breast tumors. The proportion of cases with PI3K-AKT-mTOR genomic alterations or signaling network activation were compared between hepatic and nonhepatic lesions.Results:PIK3CA mutation and activation of AKT (S473) and p70S6K (T389) were detected more frequently among liver metastases than nonhepatic lesions (P < 0.01, P = 0.056, and P = 0.053, respectively). However, PIK3CA mutations alone were insufficient in predicting protein activation (P = 0.32 and P = 0.19 for activated AKT and p70S6K, respectively). RPPA analysis of an independent cohort of 154 tumors confirmed the relationship between pathway activation and hepatic metastasis [AKT (S473), mTOR (S2448), and 4EBP1 (S65); P < 0.01, P = 0.02, and P = 0.01, respectively]. Similar results were also seen between liver metastases and primary breast tumors [AKT (S473) P < 0.01, mTOR (S2448) P < 0.01, 4EBP1 (S65) P = 0.01]. This signature was lost when primary tumors were compared with all metastatic sites combined.Conclusions: Breast cancer patients with liver metastasis may represent a molecularly homogenized cohort with increased incidence of PIK3CA mutations and activation of the PI3K-AKT-mTOR signaling network. Clin Cancer Res; 23(16); 4919-28. ©2017 AACR.

Harnessing the power of proteomics for identification of oncogenic, druggable signalling pathways in cancer

INTRODUCTION

Genomic and transcriptomic profiling of tumours has revolutionised our understanding of cancer. However, the majority of tumours possess multiple mutations, and determining which oncogene, or even which pathway, to target is difficult. Proteomics is emerging as a powerful approach to identify the functionally important pathways driving these cancers, and how they can be targeted therapeutically. Areas covered: The authors provide a technical overview of mass spectrometry based approaches for proteomic profiling, and review the current and emerging strategies available for the identification of dysregulated networks, pathways, and drug targets in cancer cells, with a key focus on the ability to profile cancer kinomes. The potential applications of mass spectrometry in the clinic are also highlighted. Expert opinion: The addition of proteomic information to genomic platforms - 'proteogenomics' - is providing unparalleled insight in cancer cell biology. Application of improved mass spectrometry technology and methodology, in particular the ability to analyse post-translational modifications (the PTMome), is providing a more complete picture of the dysregulated networks in cancer, and uncovering novel therapeutic targets. While the application of proteomics to discovery research will continue to rise, improved workflow standardisation and reproducibility is required before mass spectrometry can enter routine clinical use.

Innovations in Clinical Trial Design in the Era of Molecular Profiling

Historically, cancer has been studied, and therapeutic agents have been evaluated based on organ site, clinical staging, and histology. The science of molecular profiling has expanded our knowledge of cancer at the cellular and molecular level such that numerous subtypes are being described based on biomarker expression and genetic mutations rather than traditional classifications of the disease. Drug development has experienced a concomitant revolution in response to this knowledge with many new targeted therapeutic agents becoming available, and this has necessitated an evolution in clinical trial design. The traditional, large phase II and phase III adjuvant trial models need to be replaced with smaller, shorter, and more focused trials. These trials need to be more efficient and adaptive in order to quickly assess the efficacy of new agents and develop new companion diagnostics. We are now seeing a substantial shift from the traditional multiphase trial model to an increase in phase II adjuvant and neoadjuvant trials in earlier-stage disease incorporating surrogate endpoints for long-term survival to assess efficacy of therapeutic agents in shorter time frames. New trial designs have emerged with capabilities to assess more efficiently multiple disease types, multiple molecular subtypes, and multiple agents simultaneously, and regulatory agencies have responded by outlining new pathways for accelerated drug approval that can help bring effective targeted therapeutic agents to the clinic more quickly for patients in need.

Institutional implementation of clinical tumor profiling on an unselected cancer population

BACKGROUND. Comprehensive genomic profiling of a patient's cancer can be used to diagnose, monitor, and recommend treatment. Clinical implementation of tumor profiling in an enterprise-wide, unselected cancer patient population has yet to be reported. METHODS. We deployed a hybrid-capture and massively parallel sequencing assay (OncoPanel) for all adult and pediatric patients at our combined cancer centers. Results were categorized by pathologists based on actionability. We report the results for the first 3,727 patients tested. RESULTS. Our cohort consists of cancer patients unrestricted by disease site or stage. Across all consented patients, half had sufficient and available (>20% tumor) material for profiling; once specimens were received in the laboratory for pathology review, 73% were scored as adequate for genomic testing. When sufficient DNA was obtained, OncoPanel yielded a result in 96% of cases. 73% of patients harbored an actionable or informative alteration; only 19% of these represented a current standard of care for therapeutic stratification. The findings recapitulate those of previous studies of common cancers but also identify alterations, including in AXL and EGFR, associated with response to targeted therapies. In rare cancers, potentially actionable alterations suggest the utility of a "cancer-agnostic" approach in genomic profiling. Retrospective analyses uncovered contextual genomic features that may inform therapeutic response and examples where diagnoses revised by genomic profiling markedly changed clinical management. CONCLUSIONS. Broad sequencing-based testing deployed across an unselected cancer cohort is feasible. Genomic results may alter management in diverse scenarios; however, additional barriers must be overcome to enable precision cancer medicine on a large scale. FUNDING. This work was supported by DFCI, BWH, and the National Cancer Institute (5R33CA155554 and 5K23CA157631).

Treatment of patients with refractory metastatic cancer according to molecular profiling on tumor tissue in the clinical routine: an interim-analysis of the ONCO-T-PROFILE project

Introduction

Patients with refractory metastatic cancer have been shown to benefit from molecular profiling of tumor tissue. The ONCO-T-PROFILE project was launched in March 2014 at the Innsbruck Medical University. Within 2 years our project aims to recruit 110 patients with stage IV cancer refractory to standard therapy. Our data presented here are based on an interim-analysis.

Methods

Tumor tissue specimens were submitted for molecular profiling to the certified laboratory (Caris Life Science, USA). Druggable tumor targets were selected based on biomarker status to agents with potential clinical benefit. Clinical benefit was defined as a PFS ratio (=PFS upon treatment according to the molecular profile/ PFS upon the last prior therapy) ≥ 1.3.

Results

As of April 2015, tumors from 50 patients have been molecularly profiled and one or more targets were detectable in 48 specimens (98%). So far, 19 (38%) patients have been treated according to their molecular tumor profile. To date, 8 (42%) patients have reached a PFS ratio of ≥ 1.3.

Conclusions

We could show that molecular profiling is feasible in the clinical routine. A proportion of patients might benefit from an individualized treatment approach based on molecular profiling. As a result, we will proceed to enroll patients in ONCO-T-PROFILE.

A pilot study exploring the molecular architecture of the tumor microenvironment in human prostate cancer using laser capture microdissection and reverse phase protein microarray

The cross-talk between tumor epithelium and surrounding stromal/immune microenvironment is essential to sustain tumor growth and progression and provides new opportunities for the development of targeted treatments focused on disrupting the tumor ecology. Identification of novel approaches to study these interactions is of primary importance. Using laser capture microdissection (LCM) coupled with reverse phase protein microarray (RPPA) based protein signaling activation mapping we explored the molecular interconnection between tumor epithelium and surrounding stromal microenvironment in 18 prostate cancer (PCa) specimens. Four specimen-matched cellular compartments (normal-appearing epithelium and its adjacent stroma, and malignant epithelium and its adjacent stroma) were isolated for each case. The signaling network analysis of the four compartments unraveled a number of molecular mechanisms underlying the communication between tumor cells and stroma in the context of the tumor microenvironment. In particular, differential expression of inflammatory mediators like IL-8 and IL-10 by the stroma cells appeared to modulate specific cross-talks between the tumor cells and surrounding microenvironment.

Clinical Outcomes of Patients with Rare and Heavily Pretreated Solid Tumors Treated according to the Results of Tumor Molecular Profiling

Patients with heavily pretreated advanced cancer or with rare tumors are difficult to treat. Molecular profiling (MP) of tumors to identify biomarkers that predict potential outcomes with individual therapies is an emerging strategy to guide treatment decisions. Patients with rare tumors for which standard-of-care therapy was unavailable or more common tumors for which standard-of-care options had been exhausted underwent MP at a single Australian center. Data regarding treating physicians' choice of therapy, MP results and recommendations, and patient outcomes were collected. Seven patients had received prior standard first-line therapy (PST), 16 had rare tumors, and 31 had been heavily pretreated (HPT; ≥2 prior lines). Most treatments suggested by MP (541/594; 91.1%) were common chemotherapy drugs available in generic formulations. MP-guided therapy recommendations differed from physician's recommendations in 48 patients (88.9%). MP-guided therapy produced clinical benefit (improved QOL and/or performance status, symptoms, bodyweight, or RECIST) in 19/31 (61.3%), 11/16 (68.8%), and 3/7 (42.9%) patients with HPTs, rare tumors, and PSTs, respectively, and had a PFS ratio ≥1.3 in 22/37 evaluable patients (59.5%; 95% confidence interval 44-76%). The null hypothesis that ≤15% of these patients would have a PFS ratio ≥1.3 was rejected (one-sided p < 0.0001). In conclusion, using MP to guide therapy selection is feasible in clinical practice and may improve patient outcomes.

The Obama Administration's Cancer Moonshot: A Call for Proteomics

The Cancer Moonshot Program has been launched and represents a potentially paradigm-shifting initiative with the goal to implement a focused national effort to double the rate of progress against cancer. The placement of precision medicine, immunotherapy, genomics, and combination therapies was placed at the central nexus of this initiative. Although we are extremely enthusiastic about the goals of the program, it is time we meet this revolutionary project with equally bold and cutting-edge ideas: it is time we move firmly into the postgenome era and provide the necessary resources to propel and seize on innovative recent gains in the field of proteomics required for it to stand on equal footing in this narrative as a combined, synergistic engine for molecular profiling. After all, although the genome is the information archive, it is the proteins that actually do the work of the cell and represent the structural cellular machinery. It is the proteins that comprise most of the biomarkers that are measured to detect cancers, constitute the antigens that drive immune response and inter- and intracellular communications, and it is the proteins that are the drug targets for nearly every targeted therapy that is being evaluated in cancer trials today. We believe that a combined systems biology view of the tumor microenvironment that orients cancer studies back to the functional proteome, phosphoproteome, and biochemistry of the cell will be essential to deliver on the promise of the Cancer Moonshot Program. Clin Cancer Res; 22(18); 4556-8. ©2016 AACR.