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<p>Human tumors are diverse in their natural history and response to treatment, which in part results from genetic and transcriptomic heterogeneity. In clinical practice, single-site needle biopsies are used to sample this diversity, but cancer biomarkers may be confounded by spatiogenomic heterogeneity within individual tumors. Here we investigate clonally expressed genes as a solution to the sampling bias problem by analyzing multiregion whole-exome and RNA sequencing data for 450 tumor regions from 184 patients with lung adenocarcinoma in the TRACERx study. We prospectively validate the survival association of a clonal expression biomarker, Outcome Risk Associated Clonal Lung Expression (ORACLE), in combination with clinicopathological risk factors, and in stage I disease. We expand our mechanistic understanding, discovering that clonal transcriptional signals are detectable before tissue invasion, act as a molecular fingerprint for lethal metastatic clones and predict chemotherapy sensitivity. Lastly, we find that ORACLE summarizes the prognostic information encoded by genetic evolutionary measures, including chromosomal instability, as a concise 23-transcript assay.</p>

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Prospective validation of ORACLE, a clonal expression biomarker associated with survival of patients with lung adenocarcinoma

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  • 发表日期：

    2025年1月9日

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  • Dhruva Biswas,
  • Yun-Hsin Liu,
  • Javier Herrero,
  • Yin Wu,
  • David A. Moore,
  • Takahiro Karasaki,
  • Kristiana Grigoriadis,
  • Wei-Ting Lu,
  • Selvaraju Veeriah,
  • Cristina Naceur-Lombardelli,
  • Neil Magno,
  • Sophia Ward,
  • Alexander M. Frankell,
  • Mark S. Hill,
  • Emma Colliver,
  • Sophie de Carné Trécesson,
  • Philip East,
  • Aman Malhi,
  • Daniel M. Snell,
  • Olga O’Neill,
  • Daniel Leonce,
  • Johanna Mattsson,
  • Amanda Lindberg,
  • Patrick Micke,
  • Judit Moldvay,
  • Zsolt Megyesfalvi,
  • Balazs Dome,
  • János Fillinger,
  • Jerome Nicod,
  • Julian Downward,
  • Zoltan Szallasi,
  • Ariana Huebner,
  • Corentin Richard,
  • Crispin T. Hiley,
  • Emilia L. Lim,
  • Francisco Gimeno-Valiente,
  • Krupa Thakkar,
  • Maise Al Bakir,
  • Monica Sivakumar,
  • Ieva Usaite,
  • Sadegh Saghafinia,
  • Sharon Vanloo,
  • Sian Harries,
  • Antonia Toncheva,
  • Paulina Prymas,
  • Bushra Mussa,
  • Michalina Magala,
  • Elizabeth Keene,
  • Abigail Bunkum,
  • Carlos Martínez-Ruiz,
  • Clare Puttick,
  • Despoina Karagianni,
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  • Olivia Lucas,
  • Robert Bentham,
  • Roberto Vendramin,
  • Sergio A. Quezada,
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  • Sonya Hessey,
  • Supreet Kaur Bola,
  • Wing Kin Liu,
  • Rija Zaidi,
  • Lucrezia Patruno,
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  • Siow Ming Lee,
  • Gareth A. Wilson,
  • Rachel Rosenthal,
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  • Chris Bailey,
  • Claudia Lee,
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  • Oriol Pich,
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  • Maria Zagorulya,
  • Michelle M. Leung,
  • Teresa Marafioti,
  • Elaine Borg,
  • Mary Falzon,
  • Reena Khiroya,
  • Thomas Patrick Jones,
  • Sarah Benafif,
  • Dionysis Papadatos-Pastos,
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  • Angeliki Karamani,
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  • James L. Reading,
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  • Antonio Paiva-Correia,
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  • Richard Kevin Stone,
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  • Kunal Bhakhri,
  • Pat Gorman,
  • Robert C. M. Stephens,
  • Yien Ning Sophia Wong,
  • Maria Chiara Pisciella,
  • Steve Bandula,
  • Thomas B. K. Watkins,
  • Catarina Veiga,
  • Gary Royle,
  • Charles-Antoine Collins-Fekete,
  • Francesco Fraioli,
  • Paul Ashford,
  • Alexander James Procter,
  • Asia Ahmed,
  • Magali N. Taylor,
  • Arjun Nair,
  • David Lawrence,
  • Davide Patrini,
  • Neal Navani,
  • Ricky M. Thakrar,
  • Sam M. Janes,
  • Zoltan Kaplar,
  • Allan Hackshaw,
  • Camilla Pilotti,
  • Rachel Leslie,
  • Anne-Marie Hacker,
  • Sean Smith,
  • Aoife Walker,
  • Anca Grapa,
  • Hanyun Zhang,
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摘要

Human tumors are diverse in their natural history and response to treatment, which in part results from genetic and transcriptomic heterogeneity. In clinical practice, single-site needle biopsies are used to sample this diversity, but cancer biomarkers may be confounded by spatiogenomic heterogeneity within individual tumors. Here we investigate clonally expressed genes as a solution to the sampling bias problem by analyzing multiregion whole-exome and RNA sequencing data for 450 tumor regions from 184 patients with lung adenocarcinoma in the TRACERx study. We prospectively validate the survival association of a clonal expression biomarker, Outcome Risk Associated Clonal Lung Expression (ORACLE), in combination with clinicopathological risk factors, and in stage I disease. We expand our mechanistic understanding, discovering that clonal transcriptional signals are detectable before tissue invasion, act as a molecular fingerprint for lethal metastatic clones and predict chemotherapy sensitivity. Lastly, we find that ORACLE summarizes the prognostic information encoded by genetic evolutionary measures, including chromosomal instability, as a concise 23-transcript assay.