The efficacy of chemotherapy is limited by intratumoral senescent cells expressing PD-L2.

Chemotherapy often generates intratumoral senescent cancer cells that strongly modify the tumor microenvironment, favoring immunosuppression and tumor growth. We discovered, through an unbiased proteomics screen, that the immune checkpoint inhibitor programmed cell death 1 ligand 2 (PD-L2) is highly upregulated upon induction of senescence in different types of cancer cells. PD-L2 is not required for cells to undergo senescence, but it is critical for senescent cells to evade the immune system and persist intratumorally. Indeed, after chemotherapy, PD-L2-deficient senescent cancer cells are rapidly eliminated and tumors do not produce the senescence-associated chemokines CXCL1 and CXCL2. Accordingly, PD-L2-deficient pancreatic tumors fail to recruit myeloid-derived suppressor cells and undergo regression driven by CD8 T cells after chemotherapy. Finally, antibody-mediated blockade of PD-L2 strongly synergizes with chemotherapy causing remission of mammary tumors in mice. The combination of chemotherapy with anti-PD-L2 provides a therapeutic strategy that exploits vulnerabilities arising from therapy-induced senescence.

Machine learning identifies experimental brain metastasis subtypes based on their influence on neural circuits.

A high percentage of patients with brain metastases frequently develop neurocognitive symptoms; however, understanding how brain metastasis co-opts the function of neuronal circuits beyond a tumor mass effect remains unknown. We report a comprehensive multidimensional modeling of brain functional analyses in the context of brain metastasis. By testing different preclinical models of brain metastasis from various primary sources and oncogenic profiles, we dissociated the heterogeneous impact on local field potential oscillatory activity from cortical and hippocampal areas that we detected from the homogeneous inter-model tumor size or glial response. In contrast, we report a potential underlying molecular program responsible for impairing neuronal crosstalk by scoring the transcriptomic and mutational profiles in a model-specific manner. Additionally, measurement of various brain activity readouts matched with machine learning strategies confirmed model-specific alterations that could help predict the presence and subtype of metastasis.

PanDrugs2: prioritizing cancer therapies using integrated individual multi-omics data.

Genomics studies routinely confront researchers with long lists of tumor alterations detected in patients. Such lists are difficult to interpret since only a minority of the alterations are relevant biomarkers for diagnosis and for designing therapeutic strategies. PanDrugs is a methodology that facilitates the interpretation of tumor molecular alterations and guides the selection of personalized treatments. To do so, PanDrugs scores gene actionability and drug feasibility to provide a prioritized evidence-based list of drugs. Here, we introduce PanDrugs2, a major upgrade of PanDrugs that, in addition to somatic variant analysis, supports a new integrated multi-omics analysis which simultaneously combines somatic and germline variants, copy number variation and gene expression data. Moreover, PanDrugs2 now considers cancer genetic dependencies to extend tumor vulnerabilities providing therapeutic options for untargetable genes. Importantly, a novel intuitive report to support clinical decision-making is generated. PanDrugs database has been updated, integrating 23 primary sources that support >74K drug-gene associations obtained from 4642 genes and 14 659 unique compounds. The database has also been reimplemented to allow semi-automatic updates to facilitate maintenance and release of future versions. PanDrugs2 does not require login and is freely available at https://www.pandrugs.org/.

RANK is a poor prognosis marker and a therapeutic target in ER-negative postmenopausal breast cancer.

Despite strong preclinical data, the therapeutic benefit of the RANKL inhibitor, denosumab, in breast cancer patients, beyond the bone, is unclear. Aiming to select patients who may benefit from denosumab, we hereby analyzed RANK and RANKL protein expression in more than 2,000 breast tumors (777 estrogen receptor-negative, ER- ) from four independent cohorts. RANK protein expression was more frequent in ER- tumors, where it associated with poor outcome and poor response to chemotherapy. In ER- breast cancer patient-derived orthoxenografts (PDXs), RANKL inhibition reduced tumor cell proliferation and stemness, regulated tumor immunity and metabolism, and improved response to chemotherapy. Intriguingly, tumor RANK protein expression associated with poor prognosis in postmenopausal breast cancer patients, activation of NFKB signaling, and modulation of immune and metabolic pathways, suggesting that RANK signaling increases after menopause. Our results demonstrate that RANK protein expression is an independent biomarker of poor prognosis in postmenopausal and ER- breast cancer patients and support the therapeutic benefit of RANK pathway inhibitors, such as denosumab, in breast cancer patients with RANK+ ER- tumors after menopause.

Kras oncogene ablation prevents resistance in advanced lung adenocarcinomas.

KRASG12C inhibitors have revolutionized the clinical management of patients with KRASG12C-mutant lung adenocarcinoma. However, patient exposure to these inhibitors leads to the rapid onset of resistance. In this study, we have used genetically engineered mice to compare the therapeutic efficacy and the emergence of tumor resistance between genetic ablation of mutant Kras expression and pharmacological inhibition of oncogenic KRAS activity. Whereas Kras ablation induces massive tumor regression and prevents the appearance of resistant cells in vivo, treatment of KrasG12C/Trp53-driven lung adenocarcinomas with sotorasib, a selective KRASG12C inhibitor, caused a limited antitumor response similar to that observed in the clinic, including the rapid onset of resistance. Unlike in human tumors, we did not observe mutations in components of the RAS-signaling pathways. Instead, sotorasib-resistant tumors displayed amplification of the mutant Kras allele and activation of xenobiotic metabolism pathways, suggesting that reduction of the on-target activity of KRASG12C inhibitors is the main mechanism responsible for the onset of resistance. In sum, our results suggest that resistance to KRAS inhibitors could be prevented by achieving a more robust inhibition of KRAS signaling mimicking the results obtained upon Kras ablation.

PD-L1ATTAC mice reveal the potential of depleting PD-L1 expressing cells in cancer therapy.

Antibodies targeting the PD-1 receptor and its ligand PD-L1 have shown impressive responses in some tumors of bad prognosis. We hypothesized that, since immunosuppressive cells might present several immune checkpoints on their surface, the selective elimination of PD-L1 expressing cells could be efficacious in enabling the activation of antitumoral immune responses. To address this question, we developed an inducible suicidal knock-in mouse allele of Pd-l1 (PD-L1ATTAC) which allows for the tracking and specific elimination of PD-L1-expressing cells in adult tissues. Consistent with our hypothesis, elimination of PD-L1 expressing cells from the mouse peritoneum increased the septic response to lipopolysaccharide (LPS), due to an exacerbated inflammatory response to the endotoxin. In addition, mice depleted of PD-L1+ cells were resistant to colon cancer peritoneal allografts, which was associated with a loss of immunosuppressive B cells and macrophages, concomitant with an increase in activated cytotoxic CD8 T cells. Collectively, these results illustrate the usefulness of PD-L1ATTAC mice for research in immunotherapy and provide genetic support to the concept of targeting PD-L1 expressing cells in cancer.

CALR-mutated cells are vulnerable to combined inhibition of the proteasome and the endoplasmic reticulum stress response.

Cancer is driven by somatic mutations that provide a fitness advantage. While targeted therapies often focus on the mutated gene or its direct downstream effectors, imbalances brought on by cell-state alterations may also confer unique vulnerabilities. In myeloproliferative neoplasms (MPN), somatic mutations in the calreticulin (CALR) gene are disease-initiating through aberrant binding of mutant CALR to the thrombopoietin receptor MPL and ligand-independent activation of JAK-STAT signaling. Despite these mechanistic insights into the pathogenesis of CALR-mutant MPN, there are currently no mutant CALR-selective therapies available. Here, we identified differential upregulation of unfolded proteins, the proteasome and the ER stress response in CALR-mutant hematopoietic stem cells (HSCs) and megakaryocyte progenitors. We further found that combined pharmacological inhibition of the proteasome and IRE1-XBP1 axis of the ER stress response preferentially targets Calr-mutated HSCs and megakaryocytic-lineage cells over wild-type cells in vivo, resulting in an amelioration of the MPN phenotype. In serial transplantation assays following combined proteasome/IRE1 inhibition for six weeks, we did not find preferential depletion of Calr-mutant long-term HSCs. Together, these findings leverage altered proteostasis in Calr-mutant MPN to identify combinatorial dependencies that may be targeted for therapeutic benefit and suggest that eradicating disease-propagating Calr-mutant LT-HSCs may require more sustained treatment.

Nanobodies targeting ABCC3 for immunotargeted applications in glioblastoma.

The cancer "omics" reveal many clinically relevant alterations that are transforming the molecular characterization of glioblastomas. However, many of these findings are not yet translated into clinical practice due, in part, to the lack of non-invasive biomarkers and the limitations imposed by the blood-brain barrier. Nanobodies, camelid single-domain antibody fragments, emerge as a promising tool for immunotargeted applications for diagnosing and treating glioblastomas. Performing agnostic bioinformatic analysis from glioblastoma patient datasets, we identified ATP Binding Cassette subfamily C member 3 (ABCC3) as a suitable target for immunotargeted applications. The expression of ABCC3 is associated with poor survival and impaired response to temozolomide. Importantly, high expression of ABCC3 is restricted to glioblastoma, with negligible levels in healthy brain tissue, and further correlates with tumor grade and stemness markers. We identified three immunogenic epitopes of ABCC3 which were used to isolate nanobodies from a glioblastoma-specific phage-display nanobody library. Two nanobodies targeting ABCC3 (NbA42 and NbA213) were further characterized and demonstrated in vivo selective recognition of ABCC3 in glioblastoma xenograft mouse models upon systemic administration. We designate NbA42 and NbA213 as new candidates to implement immunotargeted applications guiding a more personalized and precise diagnosis, monitoring, and treatment of glioblastoma patients.

Bioinformatics roadmap for therapy selection in cancer genomics.

Tumour heterogeneity is one of the main characteristics of cancer and can be categorised into inter- or intratumour heterogeneity. This heterogeneity has been revealed as one of the key causes of treatment failure and relapse. Precision oncology is an emerging field that seeks to design tailored treatments for each cancer patient according to epidemiological, clinical and omics data. This discipline relies on bioinformatics tools designed to compute scores to prioritise available drugs, with the aim of helping clinicians in treatment selection. In this review, we describe the current approaches for therapy selection depending on which type of tumour heterogeneity is being targeted and the available next-generation sequencing data. We cover intertumour heterogeneity studies and individual treatment selection using genomics variants, expression data or multi-omics strategies. We also describe intratumour dissection through clonal inference and single-cell transcriptomics, in each case providing bioinformatics tools for tailored treatment selection. Finally, we discuss how these therapy selection workflows could be integrated into the clinical practice.

Excess weight and anti-PD-1 immune checkpoint inhibitor's outcomes in non-small cell lung cancer.

PURPOSE: Immune checkpoint inhibitors are one of the most effective treatments available in advanced non-small cell lung cancer. However, at present, there are no clinical or analytical biomarkers that define which patients benefit with certainty from these treatments. In our study, we evaluated whether excess weight could be a good predictive biomarker of benefit from these drugs. METHODS: We studied a population of 79 patients, divided into a study group with 39 patients diagnosed with non-small cell lung cancer treated with immunotherapy and 40 patients in a control group, diagnosed with different advanced cancers, treated with non-immunotherapy treatment. We analyzed according to the presence of excess weight or not, the treatment's outcome in the study group and in the control group (objective response, and progression-free and overall survival). RESULTS: In our study, we detected a better response rate to immunotherapy in patients with excess weight (62.50 vs 26.08%, OR 4.72, p = 0.02), and a better median progression-free survival (14.19 vs 5.03 months, HR 0.50, p = 0.058) and median overall survival (33.84 months vs 20.76 months, HR 0.43, p = 0.01) in the study group. These findings were specific to the immunotherapy group since in the control group, with patients who did not receive immune checkpoint inhibitors, these findings were not found. CONCLUSION: Our study suggests that patients with excess weight who receive anti-PD-1 immune checkpoint inhibitors diagnosed with non-small cell lung cancer have a better outcome. This effect is specific to patients receiving immunotherapy.

Activation of the integrated stress response is a vulnerability for multidrug-resistant FBXW7-deficient cells.

FBXW7 is one of the most frequently mutated tumor suppressors, deficiency of which has been associated with resistance to some anticancer therapies. Through bioinformatics and genome-wide CRISPR screens, we here reveal that FBXW7 deficiency leads to multidrug resistance (MDR). Proteomic analyses found an upregulation of mitochondrial factors as a hallmark of FBXW7 deficiency, which has been previously linked to chemotherapy resistance. Despite this increased expression of mitochondrial factors, functional analyses revealed that mitochondria are under stress, and genetic or chemical targeting of mitochondria is preferentially toxic for FBXW7-deficient cells. Mechanistically, the toxicity of therapies targeting mitochondrial translation such as the antibiotic tigecycline relates to the activation of the integrated stress response (ISR) in a GCN2 kinase-dependent manner. Furthermore, the discovery of additional drugs that are toxic for FBXW7-deficient cells showed that all of them unexpectedly activate a GCN2-dependent ISR regardless of their accepted mechanism of action. Our study reveals that while one of the most frequent mutations in cancer reduces the sensitivity to the vast majority of available therapies, it renders cells vulnerable to ISR-activating drugs.

Whole-genome CRISPR screening identifies N-glycosylation as a genetic and therapeutic vulnerability in CALR-mutant MPNs.

Calreticulin (CALR) mutations are frequent, disease-initiating events in myeloproliferative neoplasms (MPNs). Although the biological mechanism by which CALR mutations cause MPNs has been elucidated, there currently are no clonally selective therapies for CALR-mutant MPNs. To identify unique genetic dependencies in CALR-mutant MPNs, we performed a whole-genome clustered regularly interspaced short palindromic repeats (CRISPR) knockout depletion screen in mutant CALR-transformed hematopoietic cells. We found that genes in the N-glycosylation pathway (among others) were differentially depleted in mutant CALR-transformed cells as compared with control cells. Using a focused pharmacological in vitro screen targeting unique vulnerabilities uncovered in the CRISPR screen, we found that chemical inhibition of N-glycosylation impaired the growth of mutant CALR-transformed cells, through a reduction in MPL cell surface expression. We treated Calr-mutant knockin mice with the N-glycosylation inhibitor 2-deoxy-glucose (2-DG) and found a preferential sensitivity of Calr-mutant cells to 2-DG as compared with wild-type cells and normalization of key MPNs disease features. To validate our findings in primary human cells, we performed megakaryocyte colony-forming unit (CFU-MK) assays. We found that N-glycosylation inhibition significantly reduced CFU-MK formation in patient-derived CALR-mutant bone marrow as compared with bone marrow derived from healthy donors. In aggregate, our findings advance the development of clonally selective treatments for CALR-mutant MPNs.

Peripheral Blood Mononuclear Cells Predict Therapeutic Efficacy of Immunotherapy in NSCLC.

In lung cancer immunotherapy, biomarkers to guide clinical decisions are limited. We now explore whether the detailed immunophenotyping of circulating peripheral blood mononuclear cells (PBMCs) can predict the efficacy of anti-PD-1 immunotherapy in patients with advanced non-small-cell lung cancer (NSCLC). We determined 107 PBMCs subpopulations in a prospective cohort of NSCLC patients before starting single-agent anti-PD-1 immunotherapy (study group), analyzed by flow cytometry. As a control group, we studied patients with advanced malignancies before initiating non-immunotherapy treatment. The frequency of PBMCs was correlated with treatment outcome. Patients were categorized as having either high or low expression for each biomarker, defined as those above the 55th or below the 45th percentile of the overall marker expression within the cohort. In the study group, three subpopulations were associated with significant differences in outcome: high pretreatment levels of circulating CD4+CCR9+, CD4+CCR10+, or CD8+CXCR4+ T cells correlated with poorer overall survival (15.7 vs. 35.9 months, HR 0.16, p = 0.003; 22.0 vs. NR months, HR 0.10, p = 0.003, and 22.0 vs. NR months, HR 0.29, p = 0.02). These differences were specific to immunotherapy-treated patients. High baseline levels of circulating T cell subpopulations related to tissue lymphocyte recruitment are associated with poorer outcomes of immunotherapy-treated advanced NSCLC patients.

IL-1 mediates microbiome-induced inflammaging of hematopoietic stem cells in mice.

Aging is associated with impaired hematopoietic and immune function caused in part by decreased fitness in the hematopoietic stem cell (HSC) population and an increased myeloid differentiation bias. The reasons for this aging-associated HSC impairment are incompletely understood. Here we demonstrate that older specific pathogen free (SPF) wild-type (WT) mice in contrast to young SPF mice produce more interleukin-1a and interleukin-1b (IL-1a/b) in steady-state bone marrow (BM), with most of the IL-1a/b being derived from myeloid BM cells. Furthermore, blood from steady-state older SPF WT mice contains higher levels of microbe-associated molecular patterns, specifically TLR4 and TLR8 ligands. In addition, BM myeloid cells from older mice produce more IL-1b in vitro, and older mice show higher and more durable IL-1a/b responses upon stimulation with lipopolysaccharide in vivo. To test whether HSC aging is driven by IL-1a/b, we evaluated HSCs from IL-1 receptor 1 (IL-1R1) knockout (KO) mice. Indeed, older HSCs from IL-1R1KO mice show significantly mitigated aging-associated inflammatory signatures. Moreover, HSCs from older IL-1R1KO and from germ-free mice maintain unbiased lymphomyeloid hematopoietic differentiation upon transplantation, thus resembling this functionality of young HSCs. Importantly, in vivo antibiotic suppression of microbiota or pharmacologic blockade of IL-1 signaling in older WT mice was similarly sufficient to reverse myeloid-biased output of their HSC populations. Collectively, our data define the microbiome/IL-1/IL-1R1 axis as a key, self-sustaining and also therapeutically partially reversible driver of HSC inflammaging.

Beyondcell: targeting cancer therapeutic heterogeneity in single-cell RNA-seq data.

We present Beyondcell, a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq data and proposing cancer-specific treatments. Our method calculates an enrichment score in a collection of drug signatures, delineating therapeutic clusters (TCs) within cellular populations. Additionally, Beyondcell determines the therapeutic differences among cell populations and generates a prioritised sensitivity-based ranking in order to guide drug selection. We performed Beyondcell analysis in five single-cell datasets and demonstrated that TCs can be exploited to target malignant cells both in cancer cell lines and tumour patients. Beyondcell is available at: https://gitlab.com/bu_cnio/beyondcell .

Inactivation of EMILIN-1 by Proteolysis and Secretion in Small Extracellular Vesicles Favors Melanoma Progression and Metastasis.

Several studies have demonstrated that melanoma-derived extracellular vesicles (EVs) are involved in lymph node metastasis; however, the molecular mechanisms involved are not completely defined. Here, we found that EMILIN-1 is proteolyzed and secreted in small EVs (sEVs) as a novel mechanism to reduce its intracellular levels favoring metastasis in mouse melanoma lymph node metastatic cells. Interestingly, we observed that EMILIN-1 has intrinsic tumor and metastasis suppressive-like properties reducing effective migration, cell viability, primary tumor growth, and metastasis. Overall, our analysis suggests that the inactivation of EMILIN-1 by proteolysis and secretion in sEVs reduce its intrinsic tumor suppressive activities in melanoma favoring tumor progression and metastasis.

Dianhydrogalactitol Overcomes Multiple Temozolomide Resistance Mechanisms in Glioblastoma.

Glioblastoma (GBM) is the most frequent and aggressive primary tumor type in the central nervous system in adults. Resistance to chemotherapy remains one of the major obstacles in GBM treatment. Identifying and overcoming the mechanisms of therapy resistance is instrumental to develop novel therapeutic approaches for patients with GBM. To determine the major drivers of temozolomide (TMZ) sensitivity, we performed shRNA screenings in GBM lines with different O6-methylguanine-DNA methyl-transferase (MGMT) status. We then evaluated dianhydrogalactitol (Val-083), a small alkylating molecule that induces interstrand DNA crosslinking, as a potential treatment to bypass TMZ-resistance mechanisms. We found that loss of mismatch repair (MMR) components and MGMT expression are mutually exclusive mechanisms driving TMZ resistance in vitro Treatment of established GBM cells and tumorsphere lines with Val-083 induces DNA damage and cell-cycle arrest in G2-M phase, independently of MGMT or MMR status, thus circumventing conventional resistance mechanisms to TMZ. Combination of TMZ and Val-083 shows a synergic cytotoxic effect in tumor cells in vitro, ex vivo, and in vivo We propose this combinatorial treatment as a potential approach for patients with GBM.

DREIMT: a drug repositioning database and prioritization tool for immunomodulation.

MOTIVATION: Drug immunomodulation modifies the response of the immune system and can be therapeutically exploited in pathologies such as cancer and autoimmune diseases. RESULTS: DREIMT is a new hypothesis-generation web tool, which performs drug prioritization analysis for immunomodulation. DREIMT provides significant immunomodulatory drugs targeting up to 70 immune cells subtypes through a curated database that integrates 4960 drug profiles and ∼2600 immune gene expression signatures. The tool also suggests potential immunomodulatory drugs targeting user-supplied gene expression signatures. Final output includes drug-signature association scores, FDRs and downloadable plots and results tables. AVAILABILITYAND IMPLEMENTATION: http://www.dreimt.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.