Genomics to select treatment for patients with metastatic breast cancer.

Cancer progression is driven in part by genomic alterations1. The genomic characterization of cancers has shown interpatient heterogeneity regarding driver alterations2, leading to the concept that generation of genomic profiling in patients with cancer could allow the selection of effective therapies3,4. Although DNA sequencing has been implemented in practice, it remains unclear how to use its results. A total of 1,462 patients with HER2-non-overexpressing metastatic breast cancer were enroled to receive genomic profiling in the SAFIR02-BREAST trial. Two hundred and thirty-eight of these patients were randomized in two trials (nos. NCT02299999 and NCT03386162) comparing the efficacy of maintenance treatment5 with a targeted therapy matched to genomic alteration. Targeted therapies matched to genomics improves progression-free survival when genomic alterations are classified as level I/II according to the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT)6 (adjusted hazards ratio (HR): 0.41, 90% confidence interval (CI): 0.27-0.61, P < 0.001), but not when alterations are unselected using ESCAT (adjusted HR: 0.77, 95% CI: 0.56-1.06, P = 0.109). No improvement in progression-free survival was observed in the targeted therapies arm (unadjusted HR: 1.15, 95% CI: 0.76-1.75) for patients presenting with ESCAT alteration beyond level I/II. Patients with germline BRCA1/2 mutations (n = 49) derived high benefit from olaparib (gBRCA1: HR = 0.36, 90% CI: 0.14-0.89; gBRCA2: HR = 0.37, 90% CI: 0.17-0.78). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with metastatic breast cancer.

The life history of 21 breast cancers.

Cancer evolves dynamically as clonal expansions supersede one another driven by shifting selective pressures, mutational processes, and disrupted cancer genes. These processes mark the genome, such that a cancer's life history is encrypted in the somatic mutations present. We developed algorithms to decipher this narrative and applied them to 21 breast cancers. Mutational processes evolve across a cancer's lifespan, with many emerging late but contributing extensive genetic variation. Subclonal diversification is prominent, and most mutations are found in just a fraction of tumor cells. Every tumor has a dominant subclonal lineage, representing more than 50% of tumor cells. Minimal expansion of these subclones occurs until many hundreds to thousands of mutations have accumulated, implying the existence of long-lived, quiescent cell lineages capable of substantial proliferation upon acquisition of enabling genomic changes. Expansion of the dominant subclone to an appreciable mass may therefore represent the final rate-limiting step in a breast cancer's development, triggering diagnosis.

Mutational processes molding the genomes of 21 breast cancers.

All cancers carry somatic mutations. The patterns of mutation in cancer genomes reflect the DNA damage and repair processes to which cancer cells and their precursors have been exposed. To explore these mechanisms further, we generated catalogs of somatic mutation from 21 breast cancers and applied mathematical methods to extract mutational signatures of the underlying processes. Multiple distinct single- and double-nucleotide substitution signatures were discernible. Cancers with BRCA1 or BRCA2 mutations exhibited a characteristic combination of substitution mutation signatures and a distinctive profile of deletions. Complex relationships between somatic mutation prevalence and transcription were detected. A remarkable phenomenon of localized hypermutation, termed "kataegis," was observed. Regions of kataegis differed between cancers but usually colocalized with somatic rearrangements. Base substitutions in these regions were almost exclusively of cytosine at TpC dinucleotides. The mechanisms underlying most of these mutational signatures are unknown. However, a role for the APOBEC family of cytidine deaminases is proposed.

Author Correction: Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

In the Methods section of this Article, 'greater than' should have been 'less than' in the sentence 'Putative regions of clustered rearrangements were identified as having an average inter-rearrangement distance that was at least 10 times greater than the whole-genome average for the individual sample. '. The Article has not been corrected.

Landscape of somatic mutations in 560 breast cancer whole-genome sequences.

We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

Signatures of mutational processes in human cancer.

All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.

A gene-expression profiling score for prediction of outcome in patients with follicular lymphoma: a retrospective training and validation analysis in three international cohorts.

BACKGROUND: Patients with follicular lymphoma have heterogeneous outcomes. Predictor models to distinguish, at diagnosis, between patients at high and low risk of progression are needed. The objective of this study was to use gene-expression profiling data to build and validate a predictive model of outcome for patients treated in the rituximab era. METHODS: A training set of fresh-frozen tumour biopsies was prospectively obtained from 160 untreated patients with high-tumour-burden follicular lymphoma enrolled in the phase 3 randomised PRIMA trial, in which rituximab maintenance was evaluated after rituximab plus chemotherapy induction (median follow-up 6·6 years [IQR 6·0-7·0]). RNA of sufficient quality was obtained for 149 of 160 cases, and Affymetrix U133 Plus 2.0 microarrays were used for gene-expression profiling. We did a multivariate Cox regression analysis to identify genes with expression levels associated with progression-free survival independently of maintenance treatment in a subgroup of 134 randomised patients. Expression levels from 95 curated genes were then determined by digital expression profiling (NanoString technology) in 53 formalin-fixed paraffin-embedded samples of the training set to compare the technical reproducibility of expression levels for each gene between technologies. Genes with high correlation (>0·75) were included in an L2-penalised Cox model adjusted on rituximab maintenance to build a predictive score for progression-free survival. The model was validated using NanoString technology to digitally quantify gene expression in 488 formalin-fixed, paraffin-embedded samples from three independent international patient cohorts from the PRIMA trial (n=178; distinct from the training cohort), the University of Iowa/Mayo Clinic Lymphoma SPORE project (n=201), and the Barcelona Hospital Clinic (n=109). All tissue samples consisted of pretreatment diagnostic biopsies and were confirmed as follicular lymphoma grade 1-3a. The patients were all treated with regimens containing rituximab and chemotherapy, possibly followed by either rituximab maintenance or ibritumomab-tiuxetan consolidation. We determined an optimum threshold on the score to predict patients at low risk and high risk of progression. The model, including the multigene score and the threshold, was initially evaluated in the three validation cohorts separately. The sensitivity and specificity of the score for the prediction of the risk of lymphoma progression at 2 years were assessed on the combined validation cohorts. FINDINGS: In the training cohort, the expression levels of 395 genes were associated with a risk of progression. 23 genes reflecting both B-cell biology and tumour microenvironment with correlation coefficients greater than 0·75 between the two technologies and sample types were retained to build a predictive model that identified a population at an increased risk of progression (p<0·0001). In a multivariate Cox model for progression-free survival adjusted on rituximab maintenance treatment and Follicular Lymphoma International Prognostic Index 1 (FLIPI-1) score, this predictor independently predicted progression (adjusted hazard ratio [aHR] of the high-risk group compared with the low-risk group 3·68, 95% CI 2·19-6·17 [p<0·0001]). The 5-year progression-free survival was 26% (95% CI 16-43) in the high-risk group and 73% (64-83) in the low-risk group. The predictor performances were confirmed in each of the individual validation cohorts (aHR comparing high-risk to low-risk groups 2·57 [95% CI 1·65-4·01] in cohort 1; 2·12 [1·32-3·39] in cohort 2; and 2·11 [1·01-4·41] in cohort 3). In the combined validation cohort, the median progression-free survival was 3·1 years (95% CI 2·4-4·8) in the high-risk group and 10·8 years (10·1-not reached) in the low-risk group (p<0·0001). The risk of lymphoma progression at 2 years was 38% (95% CI 29-46) in the high-risk group and 19% (15-24) in the low-risk group. In a multivariate analysis, the score predicted progression-free survival independently of anti-CD20 maintenance treatment and of the FLIPI score (aHR for the combined cohort 2·30, 95% CI 1·72-3·07). INTERPRETATION: We developed and validated a robust 23-gene expression-based predictor of progression-free survival that is applicable to routinely available formalin-fixed, paraffin-embedded tumour biopsies from patients with follicular lymphoma at time of diagnosis. Applying this score could allow individualised therapy for patients according to their risk category. FUNDING: Roche, SIRIC Lyric, LYSARC, National Institutes of Health, the Henry J Predolin Foundation, and the Spanish Plan Nacional de Investigacion.

The landscape of cancer genes and mutational processes in breast cancer.

All cancers carry somatic mutations in their genomes. A subset, known as driver mutations, confer clonal selective advantage on cancer cells and are causally implicated in oncogenesis, and the remainder are passenger mutations. The driver mutations and mutational processes operative in breast cancer have not yet been comprehensively explored. Here we examine the genomes of 100 tumours for somatic copy number changes and mutations in the coding exons of protein-coding genes. The number of somatic mutations varied markedly between individual tumours. We found strong correlations between mutation number, age at which cancer was diagnosed and cancer histological grade, and observed multiple mutational signatures, including one present in about ten per cent of tumours characterized by numerous mutations of cytosine at TpC dinucleotides. Driver mutations were identified in several new cancer genes including AKT2, ARID1B, CASP8, CDKN1B, MAP3K1, MAP3K13, NCOR1, SMARCD1 and TBX3. Among the 100 tumours, we found driver mutations in at least 40 cancer genes and 73 different combinations of mutated cancer genes. The results highlight the substantial genetic diversity underlying this common disease.

A Systematic Evaluation of Blood Serum and Plasma Pre-Analytics for Metabolomics Cohort Studies.

The recent thriving development of biobanks and associated high-throughput phenotyping studies requires the elaboration of large-scale approaches for monitoring biological sample quality and compliance with standard protocols. We present a metabolomic investigation of human blood samples that delineates pitfalls and guidelines for the collection, storage and handling procedures for serum and plasma. A series of eight pre-processing technical parameters is systematically investigated along variable ranges commonly encountered across clinical studies. While metabolic fingerprints, as assessed by nuclear magnetic resonance, are not significantly affected by altered centrifugation parameters or delays between sample pre-processing (blood centrifugation) and storage, our metabolomic investigation highlights that both the delay and storage temperature between blood draw and centrifugation are the primary parameters impacting serum and plasma metabolic profiles. Storing the blood drawn at 4 °C is shown to be a reliable routine to confine variability associated with idle time prior to sample pre-processing. Based on their fine sensitivity to pre-analytical parameters and protocol variations, metabolic fingerprints could be exploited as valuable ways to determine compliance with standard procedures and quality assessment of blood samples within large multi-omic clinical and translational cohort studies.

Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open-label, proof-of-concept, randomised, controlled phase 2 trial.

BACKGROUND: Molecularly targeted agents have been reported to have anti-tumour activity for patients whose tumours harbour the matching molecular alteration. These results have led to increased off-label use of molecularly targeted agents on the basis of identified molecular alterations. We assessed the efficacy of several molecularly targeted agents marketed in France, which were chosen on the basis of tumour molecular profiling but used outside their indications, in patients with advanced cancer for whom standard-of-care therapy had failed. METHODS: The open-label, randomised, controlled phase 2 SHIVA trial was done at eight French academic centres. We included adult patients with any kind of metastatic solid tumour refractory to standard of care, provided they had an Eastern Cooperative Oncology Group performance status of 0 or 1, disease that was accessible for a biopsy or resection of a metastatic site, and at least one measurable lesion. The molecular profile of each patient's tumour was established with a mandatory biopsy of a metastatic tumour and large-scale genomic testing. We only included patients for whom a molecular alteration was identified within one of three molecular pathways (hormone receptor, PI3K/AKT/mTOR, RAF/MEK), which could be matched to one of ten regimens including 11 available molecularly targeted agents (erlotinib, lapatinib plus trastuzumab, sorafenib, imatinib, dasatinib, vemurafenib, everolimus, abiraterone, letrozole, tamoxifen). We randomly assigned these patients (1:1) to receive a matched molecularly targeted agent (experimental group) or treatment at physician's choice (control group) by central block randomisation (blocks of size six). Randomisation was done centrally with a web-based response system and was stratified according to the Royal Marsden Hospital prognostic score (0 or 1 vs 2 or 3) and the altered molecular pathway. Clinicians and patients were not masked to treatment allocation. Treatments in both groups were given in accordance with the approved product information and standard practice protocols at each institution and were continued until evidence of disease progression. The primary endpoint was progression-free survival in the intention-to-treat population, which was not assessed by independent central review. We assessed safety in any patients who received at least one dose of their assigned treatment. This trial is registered with ClinicalTrials.gov, number NCT01771458. FINDINGS: Between Oct 4, 2012, and July 11, 2014, we screened 741 patients with any tumour type. 293 (40%) patients had at least one molecular alteration matching one of the 10 available regimens. At the time of data cutoff, Jan 20, 2015, 195 (26%) patients had been randomly assigned, with 99 in the experimental group and 96 in the control group. All patients in the experimental group started treatment, as did 92 in the control group. Two patients in the control group received a molecularly targeted agent: both were included in their assigned group for efficacy analyses, the patient who received an agent that was allowed in the experimental group was included in the experimental group for the purposes of safety analyses, while the other patient, who received a molecularly targeted agent and chemotherapy, was kept in the control group for safety analyses. Median follow-up was 11·3 months (IQR 5·8-11·6) in the experimental group and 11·3 months (8·1-11·6) in the control group at the time of the primary analysis of progression-free survival. Median progression-free survival was 2·3 months (95% CI 1·7-3·8) in the experimental group versus 2·0 months (1·8-2·1) in the control group (hazard ratio 0·88, 95% CI 0·65-1·19, p=0·41). In the safety population, 43 (43%) of 100 patients treated with a molecularly targeted agent and 32 (35%) of 91 patients treated with cytotoxic chemotherapy had grade 3-4 adverse events (p=0·30). INTERPRETATION: The use of molecularly targeted agents outside their indications does not improve progression-free survival compared with treatment at physician's choice in heavily pretreated patients with cancer. Off-label use of molecularly targeted agents should be discouraged, but enrolment in clinical trials should be encouraged to assess predictive biomarkers of efficacy.

Added value of whole-exome and RNA sequencing in advanced and refractory cancer patients with no molecular-based treatment recommendation based on a 90-gene panel.

INTRODUCTION: The objective was to determine the added value of comprehensive molecular profile by whole-exome and RNA sequencing (WES/RNA-Seq) in advanced and refractory cancer patients who had no molecular-based treatment recommendation (MBTR) based on a more limited targeted gene panel (TGP) plus array-based comparative genomic hybridization (aCGH). MATERIALS AND METHODS: In this retrospective analysis, we selected 50 patients previously included in the PROFILER trial (NCT01774409) for which no MBT could be recommended based on a targeted 90-gene panel and aCGH. For each patient, the frozen tumor sample mirroring the FFPE sample used for TGP/aCGH analysis were processed for WES and RNA-Seq. Data from TGP/aCGH were reanalyzed, and together with WES/RNA-Seq, findings were simultaneously discussed at a new molecular tumor board (MTB). RESULTS: After exclusion of variants of unknown significance, a total of 167 somatic molecular alterations were identified in 50 patients (median: 3 [1-10]). Out of these 167 relevant molecular alterations, 51 (31%) were common to both TGP/aCGH and WES/RNA-Seq, 19 (11%) were identified by the TGP/aCGH only and 97 (58%) were identified by WES/RNA-Seq only, including two fusion transcripts in two patients. A MBTR was provided in 4/50 (8%) patients using the information from TGP/aCGH versus 9/50 (18%) patients using WES/RNA-Seq findings. Three patients had similar recommendations based on TGP/aCGH and WES/RNA-Seq. CONCLUSIONS: In advanced and refractory cancer patients in whom no MBTR was recommended from TGP/aCGH, WES/RNA-Seq allowed to identify more alterations which may in turn, in a limited fraction of patients, lead to new MBTR.

Sorafenib in Molecularly Selected Cancer Patients: Final Analysis of the MOST-Plus Sorafenib Cohort.

BACKGROUND: MOST-plus is a multicenter, randomized, open-label, adaptive Phase II trial evaluating the clinical benefit of targeted treatments matched to molecular alteration in advanced/metastatic solid tumors. Sorafenib was tested on patients with tumors harboring sorafenib-targeted genes. METHODS: The MOST-plus trial used a randomized discontinuation design. After 12 weeks of sorafenib (400 mg, po BID), patients with progressive disease discontinued study, patients with objective response were proposed to continue sorafenib, whereas patients with stable disease (SD) were randomly assigned (1:1) to the maintenance or interruption of treatment. The primary endpoint was RECIST version 1.1 progression-free rate at 16 weeks after randomization (PFR-16w). Secondary endpoints included progression-free survival (PFS), overall survival (OS), and toxicity. Statistical analyses used a sequential Bayesian approach with interim efficacy analyses. The enrolment could be stopped in the case of a 95% probability for the estimated PFR-16w to be higher in the maintenance than in the interruption arm (NCT02029001). RESULTS: 151 patients were included, of whom 35 had SD at 12 weeks of Sorafenib. For the 35 patients with SD on sorafenib, the PFR-16w was 65% [95% credibility interval 43.4-83.7] in the continuation arm and 25% [7.8-48.1] in the interruption arm. Median PFS and OS were improved in the maintenance versus the interruption arm (mPFS: 5.6 [95%CI 1.97-6.77] months versus 2.0 [95%CI 1.61-3.91] months (p = 0.0231) and mOS: 14.3 [95%CI 8.9-23.8] versus 8.0 months [95%CI 3.5-15.2] (p = 0.0857)). CONCLUSION: Sorafenib showed activity in progressive patients with solid tumors harboring somatic genomic alterations in sorafenib-targeted genes. Continuing sorafenib when SD is achieved improves PFR compared to interruption.

Dissecting the Origin of Heterogeneity in Uterine and Ovarian Carcinosarcomas.

Gynecologic carcinosarcomas (CS) are biphasic neoplasms composed of carcinomatous (C) and sarcomatous (S) malignant components. Because of their rarity and histologic complexity, genetic and functional studies on CS are scarce and the mechanisms of initiation and development remain largely unknown. Whole-genome analysis of the C and S components reveals shared genomic alterations, thus emphasizing the clonal evolution of CS. Reconstructions of the evolutionary history of each tumor further reveal that C and S samples are composed of both ancestral cell populations and component-specific subclones, supporting a common origin followed by distinct evolutionary trajectories. However, while we do not find any recurrent genomic features associated with phenotypic divergence, transcriptomic and methylome analyses identify a common mechanism across the cohort, the epithelial-to-mesenchymal transition (EMT), suggesting a role for nongenetic factors in inflicting changes to cellular fate. Altogether, these data accredit the hypothesis that CS tumors are driven by both clonal evolution and transcriptomic reprogramming, essential for susceptibility to transdifferentiation upon encountering environmental cues, thus linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences. Significance: We have provided a detailed characterization of the genomic landscape of CS and identified EMT as a common mechanism associated with phenotypic divergence, linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences.

Multiomic analysis of malignant pleural mesothelioma identifies molecular axes and specialized tumor profiles driving intertumor heterogeneity.

Malignant pleural mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Through a large series of whole-genome sequencing data, integrated with transcriptomic and epigenomic data using multiomics factor analysis, we demonstrate that the current World Health Organization classification only accounts for up to 10% of interpatient molecular differences. Instead, the MESOMICS project paves the way for a morphomolecular classification of MPM based on four dimensions: ploidy, tumor cell morphology, adaptive immune response and CpG island methylator profile. We show that these four dimensions are complementary, capture major interpatient molecular differences and are delimited by extreme phenotypes that-in the case of the interdependent tumor cell morphology and adapted immune response-reflect tumor specialization. These findings unearth the interplay between MPM functional biology and its genomic history, and provide insights into the variations observed in the clinical behavior of patients with MPM.

Mutational characterization of individual breast tumors: TP53 and PI3K pathway genes are frequently and distinctively mutated in different subtypes.

Understanding how cancer genes are mutated in individual tumors is an important issue with potential clinical and therapeutic impact. This is especially relevant with recently developed targeted therapies since mutated genes can be targets and/or predictors. However, to date, gene mutation profiling in individual tumors is still underexplored. Breast cancer is composed of various subtypes. We presumed that this heterogeneity reflected the involvement of different molecular mechanisms including gene mutations that affect defined signaling pathways. Unlike the majority of published mutational studies, this study was aimed to draw a mutation profile in individual tumors by screening a panel of cancer genes in the same tumor. Thus, five genes frequently mutated in breast cancers: TP53, PIK3CA, PTEN, CDH1, and AKT1 were screened in each of 120 human primary breast tumors. Mutations in at least one of these genes were found in 62.5% of the tumors, of which the majority carried a single-gene mutation. Interestingly, a substantial proportion of tumors carried mutations either in TP53 or in genes of the PI3K pathway (PIK3CA or PTEN or AKT1). These two distinct mutation patterns were significantly associated to hormone receptor expression but independent of HER2 status.

Precision medicine for patients with gastro-oesophageal cancer: A subset analysis of the ProfiLER program.

BACKGROUND: Chemotherapy, anti-HER2 and PD-1 antibodies are standard treatments but only a minority of patients derive long-term benefit from these agents. METHODS: In this report we describe the mutational landscape and outcome of patients with gastroesophageal cancers enroled in the ProfiLER program. RESULTS: Adenocarcinoma (n = 86, 59%), signet-cell (n = 37, 25%) and squamous-cell (n = 21, 14%) were the dominant histology amongst 147 patients. Genomic analyses could be performed for 114 (78%) patients. The most common genomic alterations involved ERBB2 (15%), KRAS (12%), CCND1 (7%), FGFR1-3 (8%), EGFR (5%) and MET (3%), TP53 (51%) and CDKN2A/B (10%). ERBB2, MET and FGFR alterations were found exclusively in the adenocarcinoma and signet-cell subtypes, while CCND1 amplification, TP53 mutations and CDKN2A/B loss were found in both adenocarcinoma and squamous-cell subtypes. Nine patients (8%) received therapy matched to their genomic alteration, with 5 of them achieving disease control. In an exploratory analysis, patients with stage IV disease at diagnosis who had an actionable alteration had longer overall survival compared to those without. CONCLUSION: Genomic profiling for patients with advanced gastroesophageal cancers allows the identification of actionable alterations in large proportion of patients. Increased accessibility to molecularly matched therapy may improve survival in this disease.

Epithelial-to-mesenchymal transition promotes immune escape by inducing CD70 in non-small cell lung cancer.

INTRODUCTION: Epithelial-to-mesenchymal transition (EMT) is associated with tumor aggressiveness, drug resistance, and poor survival in non-small cell lung cancer (NSCLC) and other cancers. The identification of immune-checkpoint ligands (ICPLs) associated with NSCLCs that display a mesenchymal phenotype (mNSCLC) could help to define subgroups of patients who may benefit from treatment strategies using immunotherapy. METHODS: We evaluated ICPL expression in silico in 130 NSCLC cell lines. In vitro, CRISPR/Cas9-mediated knockdown and lentiviral expression were used to assess the impact of ZEB1 expression on CD70. Gene expression profiles of lung cancer samples from the TCGA (n = 1018) and a dataset from MD Anderson Cancer Center (n = 275) were analyzed. Independent validation was performed by immunohistochemistry and targeted-RNA sequencing in 154 NSCLC whole sections, including a large cohort of pulmonary sarcomatoid carcinomas (SC, n = 55). RESULTS: We uncover that the expression of CD70, a regulatory ligand from the tumor necrosis factor ligand family, is enriched in mNSCLC in vitro models. Mechanistically, the EMT-inducer ZEB1 impacted CD70 expression and fostered increased activity of the CD70 promoter. CD70 overexpression was also evidenced in mNSCLC patient tumor samples and was particularly enriched in SC, a lung cancer subtype associated with poor prognosis. In these tumors, CD70 expression was associated with decreased CD3+ and CD8+ T-cell infiltration and increased T-cell exhaustion markers. CONCLUSION: Our results provide evidence on the pivotal roles of CD70 and ZEB1 in immune escape in mNSCLC, suggesting that EMT might promote cancer progression and metastasis by not only increasing cancer cell plasticity but also reprogramming the immune response in the local tumor microenvironment.

Comprehensive Genome Profiling in Patients With Metastatic Non-Small Cell Lung Cancer: The Precision Medicine Phase II Randomized SAFIR02-Lung/IFCT 1301 Trial.

PURPOSE: Targeted therapies (TT) and immune checkpoint blockers (ICB) have revolutionized the approach to non-small cell lung cancer (NSCLC) treatment in the era of precision medicine. Their impact as switch maintenance therapy based on molecular characterization is unknown. PATIENTS AND METHODS: SAFIR02-Lung/IFCT 1301 was an open-label, randomized, phase II trial, involving 33 centers in France. We investigated eight TT (substudy-1) and one ICB (substudy-2), compared with standard-of-care as a maintenance strategy in patients with advanced EGFR, ALK wild-type (wt) NSCLC without progression after first-line chemotherapy, based on high-throughput genome analysis. The primary outcome was progression-free survival (PFS). RESULTS: Among the 175 patients randomized in substudy-1, 116 received TT (selumetinib, vistusertib, capivasertib, AZD4547, AZD8931, vandetanib, olaparib, savolitinib) and 59 standard-of-care. Median PFS was 2.7 months [95% confidence interval (CI), 1.6-2.9] with TT versus 2.7 months (1.6-4.1) with standard-of-care (HR, 0.97; 95% CI, 0.7-1.36; P = 0.87). There were no significant differences in PFS within any molecular subgroup. In substudy-2, 183 patients were randomized, 121 received durvalumab and 62 standard-of-care. Median PFS was 3.0 months (2.3-4.4) with durvalumab versus 3.0 months (2.0-5.1) with standard-of-care (HR, 0.86; 95% CI, 0.62-1.20; P = 0.38). Preplanned subgroup analysis showed an enhanced benefit with durvalumab in patients with PD-L1 tumor proportion score (TPS) ≥1%, (n = 29; HR, 0.29; 95% CI, 0.11-0.75) as compared with PD-L1 <1% (n = 31; HR, 0.71; 95% CI, 0.31-1.60; Pinteraction = 0.036). CONCLUSIONS: Molecular profiling can feasibly be implemented to guide treatment choice for the maintenance strategy in EGFR/ALK wt NSCLC; in this study it did not lead to substantial treatment benefits beyond durvalumab for PD-L1 ≥ 1 patients.

Early changes in the immune microenvironment of oral potentially malignant disorders reveal an unexpected association of M2 macrophages with oral cancer free survival.

Understanding the dynamics of the immune microenvironment is critical to the development of immuno-based strategies for the prevention of oral potentially malignant disorders transformation to oral squamous cell carcinoma (OSCC). We used laser capture microdissection and RNA-sequencing to profile the expression of 13 matched pairs of epithelial versus stromal compartments from normal mucosa, hyperplasia, dysplasia, and invasive tumors in the 4-nitroquinolein (4-NQO) murine model of oral carcinogenesis. Genes differentially expressed at each step of transformation were defined. Immune cell deconvolution and enrichment scores of various biological processes including immune-related ones were computed. Immunohistochemistry was also performed to characterize the immune infiltrates by T-cells (T-cells CD3+, helper CD4+, cytotoxic CD8+, regulatory FoxP3+), B-cells (B220+), and macrophages (M1 iNOS+, M2 CD163+) at each histological step. Enrichment of three independent M2 macrophages signatures were computed in 86 oral leukoplakia with available clinical outcome. Most gene expression changes were observed in the stromal compartment and related to immune biological processes. Immune cell deconvolution identified infiltration by the macrophage population as the most important quantitatively especially at the stage of dysplasia. In 86 patients with oral leukoplakia, three M2 macrophages signatures were independently associated with improved oral cancer-free survival. This study provides a better understanding of the dynamics of the immune microenvironment during oral carcinogenesis and highlights an unexpected association of M2 macrophages gene expression signatures with oral cancer free survival in patients with oral leukoplakia.

Exploring the Complementarity of Pancreatic Ductal Adenocarcinoma Preclinical Models.

Purpose: Compare pancreatic ductal adenocarcinoma (PDAC), preclinical models, by their transcriptome and drug response landscapes to evaluate their complementarity. Experimental Design: Three paired PDAC preclinical models-patient-derived xenografts (PDX), xenograft-derived pancreatic organoids (XDPO) and xenograft-derived primary cell cultures (XDPCC)-were derived from 20 patients and analyzed at the transcriptomic and chemosensitivity level. Transcriptomic characterization was performed using the basal-like/classical subtyping and the PDAC molecular gradient (PAMG). Chemosensitivity for gemcitabine, irinotecan, 5-fluorouracil and oxaliplatin was established and the associated biological pathways were determined using independent component analysis (ICA) on the transcriptome of each model. The selection criteria used to identify the different components was the chemosensitivity score (CSS) found for each drug in each model. Results: PDX was the most dispersed model whereas XDPO and XDPCC were mainly classical and basal-like, respectively. Chemosensitivity scoring determines that PDX and XDPO display a positive correlation for three out of four drugs tested, whereas PDX and XDPCC did not correlate. No match was observed for each tumor chemosensitivity in the different models. Finally, pathway analysis shows a significant association between PDX and XDPO for the chemosensitivity-associated pathways and PDX and XDPCC for the chemoresistance-associated pathways. Conclusions: Each PDAC preclinical model possesses a unique basal-like/classical transcriptomic phenotype that strongly influences their global chemosensitivity. Each preclinical model is imperfect but complementary, suggesting that a more representative approach of the clinical reality could be obtained by combining them. Translational Relevance: The identification of molecular signatures that underpin drug sensitivity to chemotherapy in PDAC remains clinically challenging. Importantly, the vast majority of studies using preclinical in vivo and in vitro models fail when transferred to patients in a clinical setting despite initially promising results. This study presents for the first time a comparison between three preclinical models directly derived from the same patients. We show that their applicability to preclinical studies should be considered with a complementary focus, avoiding tumor-based direct extrapolations, which might generate misleading conclusions and consequently the overlook of clinically relevant features.