Whole-Transcriptome Profiling on Small FFPE Samples: Which Sequencing Kit Should Be Used?

RNA sequencing (RNA-Seq) appears as a great tool with huge clinical potential, particularly in oncology. However, sufficient sample size is often a limiting factor and the vast majority of samples from patients with cancer are formalin-fixed paraffin-embedded (FFPE). To date, several sequencing kits are proposed for FFPE samples yet no comparison on low quantities were performed. To select the most reliable, cost-effective, and relevant RNA-Seq approach, we applied five FFPE-compatible kits (based on 3' capture, exome-capture and ribodepletion approaches) using 8 ng to 400 ng of FFPE-derived RNA and compared them to Nanostring on FFPE samples and to a reference PolyA (Truseq) approach on flash-frozen samples of the same tumors. We compared gene expression correlations and reproducibility. The Smarter Pico V3 ribodepletion approach appeared systematically the most comparable to Nanostring and Truseq (p < 0.001) and was a highly reproducible technique. In comparison with exome-capture and 3' kits, the Smarter appeared more comparable to Truseq (p < 0.001). Overall, our results suggest that the Smarter is the most robust RNA-Seq technique to study small FFPE samples and 3' Lexogen presents an interesting quality−price ratio for samples with less limiting quantities.

DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification.

BACKGROUND: Quantification of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient specificities. Bioinformatic tools to assess the different cell populations from single-omic datasets as bulk transcriptome or methylome samples have been recently developed, including reference-based and reference-free methods. Improved methods using multi-omic datasets are yet to be developed in the future and the community would need systematic tools to perform a comparative evaluation of these algorithms on controlled data. RESULTS: We present DECONbench, a standardized unbiased benchmarking resource, applied to the evaluation of computational methods quantifying cell-type heterogeneity in cancer. DECONbench includes gold standard simulated benchmark datasets, consisting of transcriptome and methylome profiles mimicking pancreatic adenocarcinoma molecular heterogeneity, and a set of baseline deconvolution methods (reference-free algorithms inferring cell-type proportions). DECONbench performs a systematic performance evaluation of each new methodological contribution and provides the possibility to publicly share source code and scoring. CONCLUSION: DECONbench allows continuous submission of new methods in a user-friendly fashion, each novel contribution being automatically compared to the reference baseline methods, which enables crowdsourced benchmarking. DECONbench is designed to serve as a reference platform for the benchmarking of deconvolution methods in the evaluation of cancer heterogeneity. We believe it will contribute to leverage the benchmarking practices in the biomedical and life science communities. DECONbench is hosted on the open source Codalab competition platform. It is freely available at: https://competitions.codalab.org/competitions/27453 .

Adrenal gland as a sanctuary site for immunotherapy in patients with microsatellite instability-high metastatic colorectal cancer.

Metastatic colorectal cancers (mCRC) harboring microsatellite instability (MSI) are sensitive to immune checkpoint inhibitors (ICIs), but the mechanisms of resistance to ICIs remain unclear. Dissociated responses in patients with ICI-treated cancer suggest that certain organs may serve as sanctuary sites due to the tumor microenvironment. This case series describes five patients with ICI-treated MSI mCRC with disease progression limited to the adrenal glands. At ICI initiation, three patients were free of metastasis in the adrenal glands. Four patients experienced objective response per RECIST (Response Evaluation Criteria in Solid Tumors) while treated with ICI. ICI treatment was discontinued due to progressive disease limited to the adrenal glands (n=3) or toxicity (n=2). The time between ICI initiation and progression in the adrenal glands ranged from 11 to 39 months. Adrenalectomy (n=3) and stereotactic body radiation therapy (n=2) were performed. At the last follow-up, all patients were alive and progression free. Molecular analyses were performed in one patient. A significant impairment of the antigen presentation pathway was observed in the ICI-resistant lesion of the adrenal gland, which could be explained by the presence of glucocorticoids in the adrenal gland microenvironment. We also detected an overexpression of TSC22D3, a glucocorticoid-target gene that functions as a mediator of anti-inflammation and immunosuppression. This case series suggests that the adrenal glands may be the sanctuary sites for ICI-treated MSI mCRC through the glucocorticoid-induced impairment of the antigen presentation machinery.

Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer.

BACKGROUND: A significant gap in pancreatic ductal adenocarcinoma (PDAC) patient's care is the lack of molecular parameters characterizing tumours and allowing a personalized treatment. METHODS: Patient-derived xenografts (PDX) were obtained from 76 consecutive PDAC and classified according to their histology into five groups. A PDAC molecular gradient (PAMG) was constructed from PDX transcriptomes recapitulating the five histological groups along a continuous gradient. The prognostic and predictive value for PMAG was evaluated in: i/ two independent series (n = 598) of resected tumours; ii/ 60 advanced tumours obtained by diagnostic EUS-guided biopsy needle flushing and iii/ on 28 biopsies from mFOLFIRINOX treated metastatic tumours. FINDINGS: A unique transcriptomic signature (PAGM) was generated with significant and independent prognostic value. PAMG significantly improves the characterization of PDAC heterogeneity compared to non-overlapping classifications as validated in 4 independent series of tumours (e.g. 308 consecutive resected PDAC, uHR=0.321 95% CI [0.207-0.5] and 60 locally-advanced or metastatic PDAC, uHR=0.308 95% CI [0.113-0.836]). The PAMG signature is also associated with progression under mFOLFIRINOX treatment (Pearson correlation to tumour response: -0.67, p-value < 0.001). INTERPRETATION: PAMG unify all PDAC pre-existing classifications inducing a shift in the actual paradigm of binary classifications towards a better characterization in a gradient. FUNDING: Project funding was provided by INCa (Grants number 2018-078 and 2018-079, BACAP BCB INCa_6294), Canceropole PACA, DGOS (labellisation SIRIC), Amidex Foundation, Fondation de France, INSERM and Ligue Contre le Cancer.

Dissecting heterogeneity in malignant pleural mesothelioma through histo-molecular gradients for clinical applications.

Malignant pleural mesothelioma (MPM) is recognized as heterogeneous based both on histology and molecular profiling. Histology addresses inter-tumor and intra-tumor heterogeneity in MPM and describes three major types: epithelioid, sarcomatoid and biphasic, a combination of the former two types. Molecular profiling studies have not addressed intra-tumor heterogeneity in MPM to date. Here, we use a deconvolution approach and show that molecular gradients shed new light on the intra-tumor heterogeneity of MPM, leading to a reconsideration of MPM molecular classifications. We show that each tumor can be decomposed as a combination of epithelioid-like and sarcomatoid-like components whose proportions are highly associated with the prognosis. Moreover, we show that this more subtle way of characterizing MPM heterogeneity provides a better understanding of the underlying oncogenic pathways and the related epigenetic regulation and immune and stromal contexts. We discuss the implications of these findings for guiding therapeutic strategies, particularly immunotherapies and targeted therapies.

Integrated molecular characterization of chondrosarcoma reveals critical determinants of disease progression.

Chondrosarcomas are primary cancers of cartilaginous tissue with highly contrasting prognoses. These tumors are defined by recurrent mutations in the IDH genes and other genetic alterations including inactivation of CDKN2A and COL2A1; however, these have no clinical value. Here we use multi-omics molecular profiles from a series of cartilage tumors and find an mRNA classification that identifies two subtypes of chondrosarcomas defined by a balance in tumor differentiation and cell cycle activation. The microRNA classification reveals the importance of the loss of expression of the 14q32 locus in defining the level of malignancy. Finally, DNA methylation is associated with IDH mutations. We can use the multi-omics classifications to predict outcome. We propose an mRNA-only classifier to reproduce the integrated multi-omics classification, and its application to relapsed tumor samples shows the progressive nature of the classification. Thus, it may be possible to use mRNA-based signatures to detect patients with high-risk chondrosarcomas.

Identification of Positively and Negatively Selected Driver Gene Mutations Associated With Colorectal Cancer With Microsatellite Instability.

Background & Aims: Recent studies have shown that cancers arise as a result of the positive selection of driver somatic events in tumor DNA, with negative selection playing only a minor role, if any. However, these investigations were concerned with alterations at nonrepetitive sequences and did not take into account mutations in repetitive sequences that have very high pathophysiological relevance in the tumors showing microsatellite instability (MSI) resulting from mismatch repair deficiency investigated in the present study. Methods: We performed whole-exome sequencing of 47 MSI colorectal cancers (CRCs) and confirmed results in an independent cohort of 53 MSI CRCs. We used a probabilistic model of mutational events within microsatellites, while adapting pre-existing models to analyze nonrepetitive DNA sequences. Negatively selected coding alterations in MSI CRCs were investigated for their functional and clinical impact in CRC cell lines and in a third cohort of 164 MSI CRC patients. Results: Both positive and negative selection of somatic mutations in DNA repeats was observed, leading us to identify the expected true driver genes associated with the MSI-driven tumorigenic process. Several coding negatively selected MSI-related mutational events (n = 5) were shown to have deleterious effects on tumor cells. In the tumors in which deleterious MSI mutations were observed despite the negative selection, they were associated with worse survival in MSI CRC patients (hazard ratio, 3; 95% CI, 1.1-7.9; P = .03), suggesting their anticancer impact should be offset by other as yet unknown oncogenic processes that contribute to a poor prognosis. Conclusions: The present results identify the positive and negative driver somatic mutations acting in MSI-driven tumorigenesis, suggesting that genomic instability in MSI CRC plays a dual role in achieving tumor cell transformation. Exome sequencing data have been deposited in the European genome-phenome archive (accession: EGAS00001002477).

Distinct epigenetic landscapes underlie the pathobiology of pancreatic cancer subtypes.

Recent studies have offered ample insight into genome-wide expression patterns to define pancreatic ductal adenocarcinoma (PDAC) subtypes, although there remains a lack of knowledge regarding the underlying epigenomics of PDAC. Here we perform multi-parametric integrative analyses of chromatin immunoprecipitation-sequencing (ChIP-seq) on multiple histone modifications, RNA-sequencing (RNA-seq), and DNA methylation to define epigenomic landscapes for PDAC subtypes, which can predict their relative aggressiveness and survival. Moreover, we describe the state of promoters, enhancers, super-enhancers, euchromatic, and heterochromatic regions for each subtype. Further analyses indicate that the distinct epigenomic landscapes are regulated by different membrane-to-nucleus pathways. Inactivation of a basal-specific super-enhancer associated pathway reveals the existence of plasticity between subtypes. Thus, our study provides new insight into the epigenetic landscapes associated with the heterogeneity of PDAC, thereby increasing our mechanistic understanding of this disease, as well as offering potential new markers and therapeutic targets.

Pancreatic Adenocarcinoma Therapeutic Targets Revealed by Tumor-Stroma Cross-Talk Analyses in Patient-Derived Xenografts.

Preclinical models based on patient-derived xenografts have remarkable specificity in distinguishing transformed human tumor cells from non-transformed murine stromal cells computationally. We obtained 29 pancreatic ductal adenocarcinoma (PDAC) xenografts from either resectable or non-resectable patients (surgery and endoscopic ultrasound-guided fine-needle aspirate, respectively). Extensive multiomic profiling revealed two subtypes with distinct clinical outcomes. These subtypes uncovered specific alterations in DNA methylation and transcription as well as in signaling pathways involved in tumor-stromal cross-talk. The analysis of these pathways indicates therapeutic opportunities for targeting both compartments and their interactions. In particular, we show that inhibiting NPC1L1 with Ezetimibe, a clinically available drug, might be an efficient approach for treating pancreatic cancers. These findings uncover the complex and diverse interplay between PDAC tumors and the stroma and demonstrate the pivotal role of xenografts for drug discovery and relevance to PDAC.

Investigation of radiosensitivity gene signatures in cancer cell lines.

Intrinsic radiosensitivity is an important factor underlying radiotherapy response, but there is no method for its routine assessment in human tumours. Gene signatures are currently being derived and some were previously generated by expression profiling the NCI-60 cell line panel. It was hypothesised that focusing on more homogeneous tumour types would be a better approach. Two cell line cohorts were used derived from cervix [n = 16] and head and neck [n = 11] cancers. Radiosensitivity was measured as surviving fraction following irradiation with 2 Gy (SF2) by clonogenic assay. Differential gene expression between radiosensitive and radioresistant cell lines (SF2 median) was investigated using Affymetrix GeneChip Exon 1.0ST (cervix) or U133A Plus2 (head and neck) arrays. There were differences within cell line cohorts relating to tissue of origin reflected by expression of the stratified epithelial marker p63. Of 138 genes identified as being associated with SF2, only 2 (1.4%) were congruent between the cervix and head and neck carcinoma cell lines (MGST1 and TFPI), and these did not partition the published NCI-60 cell lines based on SF2. There was variable success in applying three published radiosensitivity signatures to our cohorts. One gene signature, originally trained on the NCI-60 cell lines, did partially separate sensitive and resistant cell lines in all three cell line datasets. The findings do not confirm our hypothesis but suggest that a common transcriptional signature can reflect the radiosensitivity of tumours of heterogeneous origins.

Poor prognosis associated with human papillomavirus α7 genotypes in cervical carcinoma cannot be explained by intrinsic radiosensitivity.

PURPOSE: To investigate the relationship between human papillomavirus (HPV) genotype and outcome after radiation therapy and intrinsic radiosensitivity. METHODS AND MATERIALS: HPV genotyping was performed on cervix biopsies by polymerase chain reaction using SPF-10 broad-spectrum primers, followed by deoxyribonucleic acid enzyme immunoassay and genotyping by reverse hybridization line probe assay (LiPA25) (version 1) (n=202). PapilloCheck and quantitative reverse transcription-polymerase chain reaction were used to genotype cervix cancer cell lines (n=16). Local progression-free survival after radiation therapy alone was assessed using log-rank and Cox proportionate hazard analyses. Intrinsic radiosensitivity was measured as surviving fraction at 2 Gy (SF2) using clonogenic assays. RESULTS: Of the 202 tumors, 107 (53.0%) were positive for HPV16, 29 (14.4%) for HPV18, 9 (4.5%) for HPV45, 23 (11.4%) for other HPV genotypes, and 22 (10.9%) were negative; 11 (5.5%) contained multiple genotypes, and 1 tumor was HPV X (0.5%). In 148 patients with outcome data, those with HPVα9-positive tumors had better local progression-free survival compared with α7 patients in univariate (P<.004) and multivariate (hazard ratio 1.54, 95% confidence interval 1.11-1.76, P=.021) analyses. There was no difference in the median SF2 of α9 and α7 cervical tumors (n=63). In the cell lines, 9 were α7 and 4 α9 positive and 3 negative. There was no difference in SF2 between α9 and α7 cell lines (n=14). CONCLUSION: The reduced radioresponsiveness of α7 cervical tumors is not related to intrinsic radiosensitivity.