Toussaint, N. C. | Search bioRxiv

bioRxiv2022

Acquired resistance to anti-PD1 therapy in patients with NSCLC reveals changes in T cell phenotypes and MET amplification

The treatment of non-small cell lung cancer (NSCLC) patients with immune checkpoint inhibitors has prolonged their survival dramatically. However, some patients develop resistance after initial response. Here, we used imaging mass cytometry and whole exome and RNA sequencing to analyze matching tumor samples from a cohort of NSCLC patients who initially responded to immune checkpoint inhibitor therapy and later developed acquired resistance. We detected two patterns of resistance: One group of patients had reduced numbers of tumor-infiltrating CD8+ T cells and reduced expression of PD-L1 after development of resistance, whereas the other group showed high CD8+ T cell infiltration and high expression of PD-L1 and markedly elevated expression of other immune-inhibitory molecules. In two cases, we detected downregulation of type I and II IFN pathways after resistance developed, which could lead to an impaired anti-tumor immune response. This study adds to our knowledge of the mechanisms that cause resistance to immunotherapy in NSCLC patients.

cancer biology↗

bioRxiv2020

Proteogenomic heterogeneity of localized human prostate cancer progression

BackgroundTumor-specific genomic aberrations are routinely determined by high throughput genomic measurements. It remains unclear though, how complex genome alterations affect molecular networks through changing protein levels, and consequently biochemical states of tumor tissues. ResultsHere, we investigated the propagation of genomic effects along the axis of gene expression during prostate cancer progression. For that, we quantified genomic, transcriptomic and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis revealed convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devised a network-based approach that integrates perturbations across different molecular layers, which identified a sub-network consisting of nine genes whose joint activity positively correlated with increasingly aggressive tumor phenotypes and was predictive of recurrence-free survival. Further, our data revealed a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. ConclusionsThis study uncovered molecular networks with remarkably convergent alterations across tumor sites and patients, but it also exposed a diversity of network effects: we could not identify a single sub-network that was perturbed in all high-grade tumor regions.

systems biology↗