Novel Lymphocyte-Independent Antitumor Activity by PD-1 Blocking Antibody against PD-1+ Chemoresistant Lung Cancer Cells.

PURPOSE: Antibodies against the lymphocyte PD-1 (aPD-1) receptor are cornerstone agents for advanced non-small cell lung cancer (NSCLC), based on their ability to restore the exhausted antitumor immune response. Our study reports a novel, lymphocyte-independent, therapeutic activity of aPD-1 against NSCLC, blocking the tumor-intrinsic PD-1 receptors on chemoresistant cells. EXPERIMENTAL DESIGN: PD-1 in NSCLC cells was explored in vitro at baseline, including stem-like pneumospheres, and following treatment with cisplatin both at transcriptional and protein levels. PD-1 signaling and RNA sequencing were assessed. The lymphocyte-independent antitumor activity of aPD-1 was explored in vitro, by PD-1 blockade and stimulation with soluble ligand (PD-L1s), and in vivo within NSCLC xenograft models. RESULTS: We showed the existence of PD-1+ NSCLC cell subsets in cell lines and large in silico datasets (Cancer Cell Line Encyclopedia and The Cancer Genome Atlas). Cisplatin significantly increased PD-1 expression on chemo-surviving NSCLC cells (2.5-fold P = 0.0014), while the sequential treatment with anti-PD-1 Ab impaired their recovery after chemotherapy. PD-1 was found to be associated with tumor stemness features. PD-1 expression was enhanced in NSCLC stem-like pneumospheres (P < 0.0001), significantly promoted by stimulation with soluble PD-L1 (+27% ± 4, P < 0.0001) and inhibited by PD-1 blockade (-30% ± 3, P < 0.0001). The intravenous monotherapy with anti-PD-1 significantly inhibited tumor growth of NSCLC xenografts in immunodeficient mice, without the contribution of the immune system, and delayed the occurrence of chemoresistance when combined with cisplatin. CONCLUSIONS: We report first evidence of a novel lymphocyte-independent activity of anti-PD-1 antibodies in NSCLC, capable of inhibiting chemo-surviving NSCLC cells and exploitable to contrast disease relapses following chemotherapy. See related commentary by Augustin et al., p. 505.

FOXA1 regulates alternative splicing in prostate cancer.

Dysregulation of alternative splicing in prostate cancer is linked to transcriptional programs activated by AR, ERG, FOXA1, and MYC. Here, we show that FOXA1 functions as the primary orchestrator of alternative splicing dysregulation across 500 primary and metastatic prostate cancer transcriptomes. We demonstrate that FOXA1 binds to the regulatory regions of splicing-related genes, including HNRNPK and SRSF1. By controlling trans-acting factor expression, FOXA1 exploits an "exon definition" mechanism calibrating alternative splicing toward dominant isoform production. This regulation especially impacts splicing factors themselves and leads to a reduction of nonsense-mediated decay (NMD)-targeted isoforms. Inclusion of the NMD-determinant FLNA exon 30 by FOXA1-controlled oncogene SRSF1 promotes cell growth in vitro and predicts disease recurrence. Overall, we report a role for FOXA1 in rewiring the alternative splicing landscape in prostate cancer through a cascade of events from chromatin access, to splicing factor regulation, and, finally, to alternative splicing of exons influencing patient survival.

Collision of germline POLE and PMS2 variants in a young patient treated with immune checkpoint inhibitors.

The onset of multiple and metachronous tumors in young patients induces to suspect the presence of genetic variants in genes associated with tumorigenesis. We describe here the unusual case of a 16-year-old patient who developed a synchronous bifocal colorectal adenocarcinoma with distant metastases. We provide high throughput molecular characterization with whole-exome sequencing (WES) and DNA targeted sequencing of different tumoral lesions and normal tissue samples that led to unveil a germline POLE mutation (p.Ser297Cys) coexisting with the PMS2 c.2174 + 1 G > A splicing mutation. This clinical scenario defines a "POLE-LYNCH" collision syndrome, which explains the ultra-mutator phenotype observed in the tumor lesions, and the presence of MMR deficiency-associated unusual signatures. The patient was successfully treated with immune checkpoint inhibitors but subsequently developed a high-grade urothelial carcinoma cured by surgery. We complement this analysis with a transcriptomic characterization of tumoral lesions with a panel targeting 770 genes related to the tumor microenvironment and immune evasion thus getting insight on cancer progression and response to immunotherapy.

Artificial Intelligence in Bulk and Single-Cell RNA-Sequencing Data to Foster Precision Oncology.

Artificial intelligence, or the discipline of developing computational algorithms able to perform tasks that requires human intelligence, offers the opportunity to improve our idea and delivery of precision medicine. Here, we provide an overview of artificial intelligence approaches for the analysis of large-scale RNA-sequencing datasets in cancer. We present the major solutions to disentangle inter- and intra-tumor heterogeneity of transcriptome profiles for an effective improvement of patient management. We outline the contributions of learning algorithms to the needs of cancer genomics, from identifying rare cancer subtypes to personalizing therapeutic treatments.

Identification of altered biological processes in heterogeneous RNA-sequencing data by discretization of expression profiles.

Heterogeneity is a fundamental feature of complex phenotypes. So far, genomic screenings have profiled thousands of samples providing insights into the transcriptome of the cell. However, disentangling the heterogeneity of these transcriptomic Big Data to identify defective biological processes remains challenging. Here we present GSECA, a method exploiting the bimodal behavior of RNA-sequencing gene expression profiles to identify altered gene sets in heterogeneous patient cohorts. Using simulated and experimental RNA-sequencing data sets, we show that GSECA provides higher performances than other available algorithms in detecting truly altered biological processes in large cohorts. Applied to 5941 samples from 14 different cancer types, GSECA correctly identified the alteration of the PI3K/AKT signaling pathway driven by the somatic loss of PTEN and verified the emerging role of PTEN in modulating immune-related processes. In particular, we showed that, in prostate cancer, PTEN loss appears to establish an immunosuppressive tumor microenvironment through the activation of STAT3, and low PTEN expression levels have a detrimental impact on patient disease-free survival. GSECA is available at https://github.com/matteocereda/GSECA.