The evolution of lung cancer and impact of subclonal selection in TRACERx DOI Creative Commons
Alexander M. Frankell, Michelle Dietzen, Maise Al Bakir

et al.

Nature, Journal Year: 2023, Volume and Issue: 616(7957), P. 525 - 533

Published: April 12, 2023

Lung cancer is the leading cause of cancer-associated mortality worldwide

Language: Английский

Clonal Heterogeneity and Tumor Evolution: Past, Present, and the Future DOI Creative Commons
Nicholas McGranahan, Charles Swanton

Cell, Journal Year: 2017, Volume and Issue: 168(4), P. 613 - 628

Published: Feb. 1, 2017

Language: Английский

Citations

2354

Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer DOI
Vinod P. Balachandran, Marta Łuksza, Julia N. Zhao

et al.

Nature, Journal Year: 2017, Volume and Issue: 551(7681), P. 512 - 516

Published: Nov. 1, 2017

Language: Английский

Citations

991

Resistance to checkpoint blockade therapy through inactivation of antigen presentation DOI Creative Commons
Moshe Sade-Feldman, Yunxin J. Jiao, Jonathan H. Chen

et al.

Nature Communications, Journal Year: 2017, Volume and Issue: 8(1)

Published: Oct. 20, 2017

Abstract Treatment with immune checkpoint blockade (CPB) therapies often leads to prolonged responses in patients metastatic melanoma, but the common mechanisms of primary and acquired resistance these agents remain incompletely characterized have yet be validated large cohorts. By analyzing longitudinal tumor biopsies from 17 melanoma treated CPB therapies, we observed point mutations, deletions or loss heterozygosity (LOH) beta-2-microglobulin ( B2M ), an essential component MHC class I antigen presentation, 29.4% progressing disease. In two independent cohorts anti-CTLA4 anti-PD1, respectively, find that LOH is enriched threefold non-responders (~30%) compared responders (~10%) associated poorer overall survival. Loss both copies found only non-responders. likely a mechanism targeting CTLA4 PD1.

Language: Английский

Citations

847

A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy DOI
Marta Łuksza, Nadeem Riaz, Vladimir Makarov

et al.

Nature, Journal Year: 2017, Volume and Issue: 551(7681), P. 517 - 520

Published: Nov. 1, 2017

Language: Английский

Citations

583

Molecular landmarks of tumor hypoxia across cancer types DOI
Vinayak Bhandari, Christianne Hoey, Lydia Liu

et al.

Nature Genetics, Journal Year: 2019, Volume and Issue: 51(2), P. 308 - 318

Published: Jan. 7, 2019

Language: Английский

Citations

583

Resolving genetic heterogeneity in cancer DOI
Samra Turajlic, Andrea Sottoriva, Trevor A. Graham

et al.

Nature Reviews Genetics, Journal Year: 2019, Volume and Issue: 20(7), P. 404 - 416

Published: March 27, 2019

Language: Английский

Citations

559

Clonal History and Genetic Predictors of Transformation Into Small-Cell Carcinomas From Lung Adenocarcinomas DOI
Jake June-Koo Lee, Junehawk Lee, Sehui Kim

et al.

Journal of Clinical Oncology, Journal Year: 2017, Volume and Issue: 35(26), P. 3065 - 3074

Published: May 12, 2017

Purpose Histologic transformation of EGFR mutant lung adenocarcinoma (LADC) into small-cell cancer (SCLC) has been described as one the major resistant mechanisms for epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). However, molecular pathogenesis is still unclear. Methods We investigated 21 patients with advanced EGFR-mutant LADCs that were transformed TKI-resistant SCLCs. Among them, whole genome sequencing was applied nine tumors acquired at various time points from four to reconstruct their clonal evolutionary history and detect genetic predictors transformation. The findings validated by immunohistochemistry in 210 tissues. Results identified SCLCs share a common origin undergo branched trajectories. divergence SCLC ancestors LADC cells occurred before first TKI treatments, complete inactivation both RB1 TP53 observed early stages sequenced tumors. extended early-stage tissues 75 treated TKIs; Rb p53 strikingly more frequent small-cell-transformed group than nontransformed (82% v 3%; odds ratio, 131; 95% CI, 19.9 859). registered predefined cohort (n = 65), an harbored completely inactivated had 43× greater risk (relative risk, 42.8; 5.88 311). Branch-specific mutational signature analysis revealed apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC)-induced hypermutation branches toward Conclusion are out clones harbor TP53. evaluation status TKI-treated informative predicting

Language: Английский

Citations

419

Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes DOI Creative Commons
Stefan C. Dentro, Ignaty Leshchiner, Kerstin Haase

et al.

Cell, Journal Year: 2021, Volume and Issue: 184(8), P. 2239 - 2254.e39

Published: April 1, 2021

Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin, drivers ITH across cancer types are poorly understood. To address this, we extensively characterize whole-genome sequences 2,658 samples spanning 38 types. Nearly all informative (95.1%) contain evidence distinct subclonal expansions with frequent branching relationships between subclones. We observe positive selection driver mutations most identify type-specific patterns gene mutations, fusions, structural variants, copy number alterations as well dynamic changes in mutational processes expansions. Our results underline importance its tumor evolution provide pan-cancer resource comprehensively annotated events from sequencing data.

Language: Английский

Citations

397

Machine learning approaches to drug response prediction: challenges and recent progress DOI Creative Commons
George Alexandru Adam, Ladislav Rampášek, Zhaleh Safikhani

et al.

npj Precision Oncology, Journal Year: 2020, Volume and Issue: 4(1)

Published: June 15, 2020

Abstract Cancer is a leading cause of death worldwide. Identifying the best treatment using computational models to personalize drug response prediction holds great promise improve patient’s chances successful recovery. Unfortunately, task predicting very challenging, partially due limitations available data and algorithmic shortcomings. The recent advances in deep learning may open new chapter search for ultimately result more accurate tools therapy response. This review provides an overview challenges prediction, focuses on comparing machine techniques be utmost practical use clinicians non-experts. incorporation modalities such as single-cell profiling, along with that rapidly find effective combinations will likely instrumental improving cancer care.

Language: Английский

Citations

331

Tumor evolution: Linear, branching, neutral or punctuated? DOI
Alexander Davis, Ruli Gao, Nicholas Navin

et al.

Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, Journal Year: 2017, Volume and Issue: 1867(2), P. 151 - 161

Published: Jan. 19, 2017

Language: Английский

Citations

328