PO.BCS01.01 · 生物信息与计算

瘤内白色念珠菌与非小细胞肺癌（NSCLC）的缺氧和不良结局相关

Intratumoral Candida albicans associates with hypoxia and poor outcomes in non small cell lung cancer (NSCLC)

编号 63 展板 25 时间 4/19 02:00–05:00 区域 Section 3 主讲 DIPANKOR DHRUBO, PhD

分会场 Application of Bioinformatics to Cancer Biology 1

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作者与单位 Authors & Affiliations

Dipankor Chatterjee¹, Dennis J. Grencewicz², Alexander Loncar³, Ruohan Wu⁴, Alex Samouilov², Sylvain Ferrandon⁵, McKenzie Kreamer⁶, Yogita Mehra⁷, Aspen Carson⁸, Rebecca Hoyd⁸, Shiva Jahanbakhshi⁸, Fouad Choueiry⁶, Matthew Anderson⁹, Martin Benej¹⁰, Dustin Bosch¹¹, Jiangjiang (Chris) Zhu³, Jinghai Wu¹², Thèrése Bocklage¹³, Martin McCarter¹⁴, Ahmad Tarhini¹⁵, Bodour Salhia¹⁶, Christopher A. Moskaluk¹⁷, Gregory Riedlinger¹⁸, Song Yao¹⁹, Ashiq Masood²⁰, Sheetal Hardikar²¹, Mmadili N. Ilozumba²², Cornelia M. Ulrich²¹, Abdul Rafeh Naqash²³, Carlos H.F. Chan²⁴, Craig D. Shriver²⁵, Dinesh Pal Mudaranthakam²⁶, Aaditya Pallerla²⁷, Michelle Churchman²⁸, Robert J. Rounbehler²⁹, Laura Chambers⁷, Matthew F. Kalady⁵, Nicholas C. Denko³⁰, David P. Carbone³¹, Dan Spakowicz⁸

¹Molecular Genetics, The Ohio State University, Columbus, OH,²College of Medicine, The Ohio State University, Columbus, OH,³The Ohio State University, Columbus, OH,⁴The Ohio State University Wexner Medical Center, Hilliard, OH,⁵Department of Surgery, The Ohio State University College of Medicine, Columbus, OH,⁶Department of Radiation Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, OH,⁷Department of Gynecologic Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, OH,⁸Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, OH,⁹Department of Medical Genetics, University of Wisconsin-Madison, Columbus, OH,¹⁰Molecular Medicine and Therapeutics, The Ohio State University College of Medicine, Columbus, OH,¹¹Department of Pathology, University of Iowa, Iowa City, IA,¹²The Ohio State University Comprehensive Cancer Center, Department of Radiation Oncology, OH,¹³Markey Cancer Center, Lexington, KY,¹⁴University of Colorado Anschutz Medical Campus, Aurora, CO,¹⁵Moffitt Cancer Center, Tampa, FL,¹⁶USC Norris Comprehensive Cancer Center, Los Angeles, CA,¹⁷Assoc. Professor, Dept. of Pathology, University of Virginia Health System, Charlottesville, VA,¹⁸Rutgers Cancer Institute of New Jersey, New Brunswick, NJ,¹⁹Postdoctoral Res. Associate, Dept. of Cancer Prev. & Control, Roswell Park Cancer Institute, Buffalo, NY,²⁰Indiana University Simon Cancer Center, Indianapolis, IN,²¹University of Utah Huntsman Cancer Institute, Salt Lake City, UT,²²Huntsman Cancer Institute, Salt Lake, UT,²³College of Medicine, University of Oklahoma, Oklahoma, OK,²⁴Carver College of Medicine, University of Iowa, Iowa City, IA,²⁵Uniformed Services University, Bethesda, MD,²⁶University of Kansas Medical Center, Kansas, KS,²⁷College of Medicine, University of Cincinnati, Cincinnati, OH,²⁸Aster Insights, Hudson, FL,²⁹Aster Insights, Tampa, FL,³⁰Assistant Professor, Dept. of Rad. Onc., The Ohio State University Comprehensive Cancer Center, Columbus, OH,³¹The Ohio State University College of Medicine, Columbus, OH

摘要 Abstract

中文摘要

对放疗、化疗和免疫治疗的耐药性仍然是非小细胞肺癌（NSCLC）的一大挑战，新出现的证据表明肿瘤驻留微生物可能影响治疗应答。为解决这一问题，我们将患者水平建模与临床前模型中的机制研究相结合。我们首先使用一个感知污染的流程，分析了ORIEN网络内根据全面癌症护理方案（NCT03977402）收集的2,156个NSCLC肿瘤的RNA测序数据，以量化瘤内白色念珠菌（CA）并评估其对治疗结局的影响。我们开发了MEC-TX（机制性聚类治疗），这是一个数字孪生框架，用于比较接受相似治疗方案但仅在CA负荷上有所不同的患者。在约55%的肿瘤中检测到CA；高CA负荷与显著更短的总生存期相关（风险比1.6，p < 0.01），在由MEC-TX界定的放疗和化疗治疗队列中也观察到类似趋势。在校正临床协变量（年龄、性别、分期、BMI）后，CA仍然是不良生存的独立预测因子，凸显了MEC-TX分离具有生物学意义信号的能力。转录组分析显示，CA高的肿瘤具有升高的缺氧相关基因表达（p = 0.0045），提示真菌浸润与肿瘤微环境之间存在联系。为验证这一点，我们将Lewis肺癌细胞植入同基因C57BL/6小鼠体内，并对其灌胃CA、Blautia obeum（共生菌对照）或生理盐水（溶剂对照）。经EPR血氧测定并在校正肿瘤大小后，与对照组相比，CA灌胃的肿瘤显著更大（p = 0.0108），并表现出更低的pH（p = 0.024）和降低的瘤内pO₂（p = 0.051），支持CA在创建缺氧、治疗耐药生态位方面的作用。在体外，CA条件培养基在多种细胞系中赋予放射抗性（p = 0.001），提示分泌的分子是该表型的驱动因素。总之，这些发现揭示了瘤内真菌促进缺氧和治疗耐药的一种新机制，为基于微生物组的策略提供了有力的理论依据，以克服缺氧驱动的耐药并改善精准肿瘤学。

查看英文原文 English abstract

Resistance to radiation, chemotherapy, and immunotherapy remains a major challenge in non-small cell lung cancer (NSCLC), and emerging evidence suggests tumor-resident microbes may influence therapeutic response. To address this, we combined patient-level modeling with mechanistic studies in preclinical models. We first analyzed RNA-sequencing data from 2,156 NSCLC tumors collected under the Total Cancer Care Protocol (NCT03977402) within the ORIEN network using a contamination-aware pipeline to quantify intratumoral Candida albicans (CA) and assess its impact on treatment outcomes. We developed MEC-TX (Mechanistic Clustering Treatment), a digital-twin framework that compares patients receiving similar treatment regimens differing only by CA burden. CA was detected in ~55% of tumors; high CA burden was associated with significantly shorter overall survival (hazard ratio 1.6, p < 0.01), and similar trends were observed in radiation- and chemotherapy-treated cohorts defined by MEC-TX. After adjusting for clinical covariates (age, sex, stage, BMI), CA remained an independent predictor of poor survival, underscoring MEC-TX's ability to isolate biologically meaningful signals. Transcriptomic profiling revealed CA-high tumors had elevated hypoxia-related gene expression (p = 0.0045), suggesting a link between fungal infiltration and tumor microenvironment. To test this, we implanted Lewis lung carcinoma cells into syngeneic C57BL/6 mice and gavaged them with CA, Blautia obeum (commensal control), or saline (vehicle control). CA-gavaged tumors were significantly larger (p = 0.0108) and exhibited lower pH (p = 0.024) and reduced intratumoral pO₂ (p = 0.051) compared to controls, as measured by EPR oximetry, after adjusting for tumor size, supporting CA's role in creating a hypoxic, therapy-resistant niche. In vitro , CA-conditioned media conferred radioresistance across multiple cell lines (p = 0.001), implicating secreted molecules as drivers of this phenotype. Collectively, these findings reveal a novel mechanism by which intratumoral fungi promote hypoxia and treatment resistance, providing a strong rationale for microbiome-informed strategies to overcome hypoxia-driven resistance and improve precision oncology.

利益披露 Disclosure

D. Chatterjee, None.. D. Grencewicz, None.. A. Loncar, None.. R. Wu, None.. A. Samouilov, None.. S. Ferrandon, None.. M. Kreamer, None.. Y. Mehra, None.. A. Carson, None.. R. Hoyd, None.. S. Jahanbakhshi, None.. F. Choueiry, None.. M. Anderson, None.. M. Benej, None.. D. Bosch, None.. J. Zhu, None.. J. Wu, None.. T. Bocklage, None.. M. McCarter, None.. A. Tarhini, None.. B. Salhia, None.. C. A. Moskaluk, None.. G. Riedlinger, None.. S. Yao, None.. A. Masood, None.. S. Hardikar, None.. M. N. Ilozumba, None.. C. M. Ulrich, None.. A. Naqash, None.. C. D. Shriver, None.. D. Pal Mudaranthakam, None.. A. Pallerla, None.. M. Churchman, None.. L. Chambers, None.. M. F. Kalady, None.. N. C. Denko, None.. D. P. Carbone, None.. D. Spakowicz, None.

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