Cancer Research and Treatment

Original Articles

Comprehensive Driver Mutation Landscape of DLBCL Informed by Integrated Tissue and Circulating DNA Analyses: Han Zhang, Chuanyu Hong, Xinger Gao, Yilei Shi, Chuan He, Qi Li, Ruijing Hu, Xinyuan Zhang, Xingping Lang, Wenzhuo Zhuang, Bingzong Li; Received January 26, 2026 Accepted July 11, 2026 Published online July 15, 2026; DOI: https://doi.org/10.4143/crt.2026.0093 [Accepted]

Abstract PDF: Purpose
Diffuse large B-cell lymphoma (DLBCL) is genetically heterogeneous. We aimed to define a compartment-aware driver mutation landscape of DLBCL by integrating tumor tissue and circulating cell-free DNA (cfDNA) sequencing, and to assess its biological and prognostic relevance.
Materials and Methods
Somatic mutations were analyzed from targeted sequencing of tumor tissue or bone marrow and cfDNA from peripheral blood or cerebrospinal fluid, including paired tissue–liquid samples, together with whole-genome sequencing data from TCGA. Driver genes were identified using four complementary algorithms. Functional enrichment and protein–protein interaction analyses were performed. Prognostic relevance was evaluated using multigene expression–based modeling with Cox and LASSO regression in independent cohorts.
Results
Recurrent driver alterations converged on core pathogenic pathways, including B-cell receptor signaling, NF-κB activation, epigenetic regulation, and immune escape. Twenty-two high-confidence driver genes, including PIM1, KMT2D, CD79B, B2M, TP53, MYC, and EZH2, were consistently identified across clinical cohorts and supported by TCGA data. cfDNA profiling showed substantial concordance with tissue-derived drivers while revealing gene-specific differences in mutation burden and co-mutation patterns, indicating complementary capture of clinically relevant heterogeneity. Network analysis highlighted TP53, MYC, EP300, and CREBBP as central hubs. A four-gene expression–based model (MYC, PLCL1, IRF8, LNPEP) stratified patients by overall survival and modestly improved prognostic discrimination beyond the International Prognostic Index.
Conclusion
Integrated analysis of tumor tissue and cfDNA sequencing defines a clinically relevant driver framework for DLBCL. cfDNA preserves core oncogenic signals while complementing tissue profiling, supporting refined genomic risk stratification.

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Neutrophil-to-Lymphocyte Ratio and Extrahepatic Spread Predict Response and Survival in Unresectable Hepatocellular Carcinoma: Dong Yun Kim, Heechul Nam, Jun Yong Park, Sang Hoon Ahn, Sung Won Lee, Do Young Kim; Received May 8, 2026 Accepted July 3, 2026 Published online July 7, 2026; DOI: https://doi.org/10.4143/crt.2026.0498 [Accepted]

Abstract PDF: Purpose
Identifying nonresponders to atezolizumab plus bevacizumab (AB) remains challenging in unresectable hepatocellular carcinoma (uHCC). We aimed to develop and externally validate a simple risk scoring system using baseline neutrophil-to-lymphocyte ratio (NLR) and extrahepatic spread (EHS) to predict treatment outcomes.
Materials and Methods
We included 304 patients with uHCC receiving first-line AB from multiple Korean centers (discovery, n = 220; validation, n = 84). Study outcomes included objective response rate (ORR) assessed by modified Response Evaluation Criteria in Solid Tumors, overall survival (OS), and progression-free survival (PFS). Multivariable analysis identified high NLR (>4.575) and EHS as independent predictors of nonresponse. The NLR-EHS score assigned 2 points for high NLR and 1 point for EHS (range, 0–3).
Results
In the discovery cohort, the score predicted nonresponse with an area under the receiver operating characteristic curve (AUC) of 0.749 (95% CI, 0.688–0.810); ORR fell across low- (0), moderate- (1–2), and high-risk (3) groups (67.3%, 47.7%, and 8.2%; p < 0.001). Validation confirmed comparable discrimination (AUC, 0.705; 95% CI, 0.603–0.806) and a consistent ORR gradient (77.8%, 54.2%, and 22.2%; p < 0.001). The score was prognostic for OS in discovery (HR, 1.28; p = 0.003) and validation cohorts (HR, 1.45; p = 0.007), remaining significant after adjustment (adjusted HR, 1.25 and 1.61, respectively). High-risk patients had inferior median OS (6.9 vs. 17.1 months in validation).
Conclusion
The NLR-EHS score is a practical tool for stratifying nonresponse risk and survival in uHCC patients receiving AB, facilitating early identification of high-risk patients who may benefit from alternative strategies.

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Head and Neck cancer

Risk Stratification in T4 or N3 Nasopharyngeal Carcinoma: Lin-Feng Guo, Lu-Chao Zhu, Yi-Feng Yu, Zhen-Zhen Lu, Qin Lin, San-Gang Wu; Cancer Res Treat. 2026;58(3):728-737. Published online August 12, 2025; DOI: https://doi.org/10.4143/crt.2025.573

Abstract PDF PubReader ePub: Purpose
This study aimed to investigate the prognostic heterogeneity among stage III nasopharyngeal carcinoma (NPC) patients according to the 9th edition of the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) staging system to identify potential subgroups requiring tailored therapeutic strategies.
Materials and Methods
We retrospectively included stage III patients (T1-3N3 or T4N0-3) who were diagnosed with NPC between January 2015 and December 2021 according to the 9th edition of the AJCC/UICC staging system. Kaplan-Meier method and multivariable Cox regression analyses were used for statistical analysis.
Results
A total of 309 patients were included in this study. A total of 92/309 (29.8%) patients developed locoregional recurrence and/or distant metastasis with a median follow-up of 52.9 months. Those with T4N3 disease had significantly lower distant metastasis-free survival (DMFS), progression-free survival (PFS), and overall survival (OS) but comparable locoregional relapse-free survival (LRFS) to those with T1-3N3 and T4N0-2 disease. Those with T4N3 disease had comparable LRFS but significantly lower 5-year DMFS (78.7% vs. 44.7%, p < 0.001), PFS (65.7% vs. 27.6%, p < 0.001), and OS (77.1% vs. 45.9%, p < 0.001) compared to those with stage T4N0-2 and T1-3N3 diseases. Similar results were confirmed using the multivariate analysis.
Conclusion
Our study demonstrates the prognostic heterogeneity of stage III disease within the 9th edition NPC staging system. T4N3 category should be considered separately and treated as a distinct entity regardless of the staging editions.

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Breast cancer

Adjuvant Chemotherapy in Breast Cancer after Neoadjuvant Therapy: Essential or Optional?: Di Zhang, Luo Yang, Yuan Zheng, Qi Zhou; Cancer Res Treat. 2026;58(1):208-220. Published online April 24, 2025; DOI: https://doi.org/10.4143/crt.2024.1254

Abstract PDF Supplementary Material PubReader ePub

Purpose
This study aimed to evaluate the impact of postoperative adjuvant chemotherapy (AC) on survival outcomes in breast cancer (BC) patients who have already undergone neoadjuvant chemotherapy (NAC) followed by surgery.
Materials and Methods
Data from a population-based cohort (2010-2020) were analyzed for BC patients treated with NAC and surgery. Univariate and multivariate Cox regression identified prognostic factors for overall survival (OS), and a nomogram was developed and validated. Personalized scores from the nomogram were used for risk stratification to assess the effect of postoperative AC.
Results
A total of 15,921 BC patients were analyzed, with 11,144 in the training cohort and 4,777 in the validation cohort. The key prognostic indicators for OS included age, race, marital status, histological grade, BC subtype, T category, N category, type of surgery, and response to NAC (all p < 0.05). The nomogram effectively predicted individualized OS rates and stratified patients into various risk categories. Postoperative AC was found to significantly enhance OS in the high-risk subgroup (p=0.011 in the training cohort, p=0.012 in the overall population). However, for the low-risk subgroup, there was no significant survival benefit from postoperative AC (p=0.130 for the training cohort, p=0.588 for the overall population), suggesting that some patients might safely forgo unnecessary postoperative AC.
Conclusion
This study efficiently differentiates between varying levels of risk, enabling clinicians to identify patients unlikely to benefit from postoperative AC and thus reduce the likelihood of overtreatment.

Citations

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Advances in nano-drug delivery systems for targeting therapy of breast cancer
Yi Zhao, Yamin Cui, Ze Zhao
Journal of Pharmacy and Pharmacology.2026;[Epub] CrossRef

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Gynecologic cancer

Application of Machine Learning Algorithms for Risk Stratification and Efficacy Evaluation in Cervical Cancer Screening among the ASCUS/LSIL Population: Evidence from the Korean HPV Cohort Study: Heekyoung Song, Hong Yeon Lee, Shin Ah Oh, Jaehyun Seong, Soo Young Hur, Youn Jin Choi; Cancer Res Treat. 2025;57(2):547-557. Published online September 6, 2024; DOI: https://doi.org/10.4143/crt.2024.465

Abstract PDF Supplementary Material PubReader ePub

Purpose
We assessed human papillomavirus (HPV) genotype-based risk stratification and the efficacy of cytology testing for cervical cancer screening in patients with atypical squamous cells of undetermined significance (ASCUS)/low-grade squamous intraepithelial lesion (LSIL).
Materials and Methods
Between 2010 and 2021, we monitored 1,273 HPV-positive women with ASCUS/LSIL every 6 months for up to 60 months. HPV infections were categorized as persistent (HPV positivity consistently observed post-enrollment), negative (HPV negativity consistently observed post-enrollment), or non-persistent (neither consistently positive nor negative). HPV genotypes were grouped into high-risk (Hr) groups 1 (types 16, 18, 31, 33, 45, 52, and 58) and 2 (types 35, 39, 51, 56, 59, 66, and 68) and a low-risk group. Hr1 was subdivided into types (a) 16 and 18; (b) 31, 33, and 45; and (c) 52 and 58. Cox regression and machine learning (ML) algorithms were used to analyze progression rates.
Results
Among 1,273 participants, 17.6% with persistent HPV infections experienced disease progression versus no progression in the HPV-negative group (p < 0.001). Cox analysis revealed the highest hazard ratios (HRs) for Hr1-a (11.6, p < 0.001), followed by Hr1-b (9.26, p < 0.001) and Hr1-c (7.21, p < 0.001). HRs peaked at 12-24 months, with Hr1-a maintaining significance at 24-36 months (10.7, p=0.034). ML analysis identified the final cytology change pattern as the most significant factor, with 14-15 months the optimal time for detecting progression from the first examination.
Conclusion
In ASCUS/LSIL cases, follow-up strategies should be based on HPV risk types. Annual follow-up was the most effective monitoring for detecting progression/regression.

Citations

Citations to this article as recorded by

AI in Cervical Cancer Cytology Diagnostics: A Narrative Review of Cutting-Edge Studies
Daniele Giansanti, Andrea Lastrucci, Antonia Pirrera, Sandra Villani, Elisabetta Carico, Enrico Giarnieri
Bioengineering.2025; 12(7): 769. CrossRef
PTK6 mediated immune signatures revealed by single cell transcriptomic and multi omics big data analysis in cervical cancer
Fen Zhao, Huanxin Zhong, Lifang You, Yi Du, Changchang Huang
Discover Oncology.2025;[Epub] CrossRef
Clinical and Virological Profiles Associated with CINTEC® PLUS Positivity: A Data-Driven Clustering and Modeling Study
Iulian-Valentin Munteanu, Demetra Socolov, Razvan Socolov, Ana-Maria Adam, Gigi Adam, Ingrid-Andrada Vasilache, Petronela Vicoveanu, Valeriu Harabor, Anamaria Harabor, Alina-Mihaela Calin
Diagnostics.2025; 15(17): 2200. CrossRef
A Competing-Risks Approach to the Progression, Regression and Persistence of High-Grade Cervical Dysplasia in Patients over 30 Years Old—A Prospective Study
Iulian-Valentin Munteanu, Demetra Socolov, Razvan Socolov, Ana-Maria Adam, Gigi Adam, Ingrid-Andrada Vasilache, Petronela Vicoveanu, Valeriu Harabor, Anamaria Harabor, Alina-Mihaela Calin
Journal of Clinical Medicine.2025; 14(17): 6303. CrossRef
AI-Driven predictive modeling of cervical intraepithelial neoplasia severity: a comprehensive analysis with clinical adoption frameworks
Farah Farzaneh, Amir Soltani, Fatemeh Dastyar, Marzieh Mohammadi, Maryam Sadat Hosseini
BMC Cancer.2025;[Epub] CrossRef
Geneticsbiologiesingle cell and expression analysis for erectile dysfunction and cervical cancer targets
Tengfei Zhao, Yangyang Li, Huixue Liu, Chongxin Tong
Discover Oncology.2024;[Epub] CrossRef

6,416 View
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5 Web of Science
6 Crossref

Lung and Thoracic cancer

Predictive Value of Interstitial Lung Abnormalities for Postoperative Pulmonary Complications in Elderly Patients with Early-stage Lung Cancer: Won Gi Jeong, Yun-Hyeon Kim, Jong Eun Lee, In-Jae Oh, Sang Yun Song, Kum Ju Chae, Hye Mi Park; Cancer Res Treat. 2022;54(3):744-752. Published online September 28, 2021; DOI: https://doi.org/10.4143/crt.2021.772

Abstract PDF Supplementary Material PubReader ePub

Purpose
Identifying pretreatment interstitial lung abnormalities (ILAs) is important because of their predictive value for complications after lung cancer treatment. This study aimed to assess the predictive value of ILAs for postoperative pulmonary complications (PPCs) in elderly patients undergoing curative resection for early-stage non-small cell lung cancer (NSCLC).
Materials and Methods
Elderly patients (age ≥ 70 years) who underwent curative resection for pathologic stage I or II NSCLC with normal preoperative spirometry results (pre-bronchodilator forced expiratory volume in 1 s to forced vital capacity [FVC] ratio > 0.70 and FVC ≥ 80% of the predicted value) between January 2012 and December 2019 were retrospectively identified. Univariable and multivariable regression analyses were performed to assess risk factors for PPCs. The Kaplan–Meier method and log-rank test were used to analyze the relationship between ILAs and postoperative mortality. One-way analysis of variance was performed to assess the correlation between ILAs and hospital stay duration.
Results
A total of 262 patients (median age, 73 [interquartile range, 71–76] years; 132 male) were evaluated. A multivariable logistic regression model revealed that, among several relevant risk factors, fibrotic ILAs independently predicted both overall PPCs (adjusted odds ratio [OR], 4.84; 95% confidence interval [CI], 1.35–17.38; p=0.016) and major PPCs (adjusted OR, 8.72; 95% CI, 1.71–44.38; p=0.009). Fibrotic ILAs were significantly associated with higher postoperative mortality and longer hospital stay (F=5.21, p=0.006).
Conclusion
Pretreatment fibrotic ILAs are associated with PPCs, higher postoperative mortality, and longer hospital stay.

Citations

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Progression of interstitial lung abnormalities and its impact on mortality in patients with lung cancer resection
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Chinese Medical Journal Pulmonary and Critical Care Medicine.2026; 4(1): 81. CrossRef
Automated quantification of interstitial lung abnormalities and emphysema on computed tomography: a predictive marker for postoperative pulmonary complications after esophagectomy
Seong Yong Park, Yunjoo Im, Jonghoon Kim, You Jin Oh, Joonghyun Ahn, Yeong Jeong Jeon, Junghee Lee, Jong Ho Cho, Hong Kwan Kim, Yong Soo Choi, Jae Il Zo, Young Mog Shim, Hye Yun Park, Ho Yun Lee
Esophagus.2026; 23(3): 582. CrossRef
Prevalence and prognostic significance of interstitial lung abnormalities in lung cancer: A meta-analysis
Ruiyuan Yang, Haoyu Wang, Dan Liu, Weimin Li
Lung Cancer.2025; 205: 108458. CrossRef
Approach to the Evaluation and Management of Interstitial Lung Abnormalities: An Official American Thoracic Society Clinical Statement
Anna J. Podolanczuk, Gary M. Hunninghake, Kevin C. Wilson, Yet H. Khor, Fayez Kheir, Brandon Pang, Ayodeji Adegunsoye, Gretchen Cararie, Tamera J. Corte, Jim Flanagan, Gunnar Gudmundsson, Lida P. Hariri, Hiroto Hatabu, Stephen M. Humphries, Bhavika Kaul,
American Journal of Respiratory and Critical Care Medicine.2025; 211(7): 1132. CrossRef
Korean Guidelines for Diagnosis and Management of Interstitial Lung Diseases
Chul Park, Yoomi Yeo, A La Woo, Jung Wan Yoo, Goohyeon Hong, Jong Wook Shin, Sung Woo Park
Tuberculosis and Respiratory Diseases.2025; 88(4): 654. CrossRef
Pretreatment Interstitial Lung Abnormalities Detected on Abdominal Computed Tomography Scans in Prostate Cancer Patients
Hyun Jin Kim, Won Gi Jeong, Jeong Yeop Lee, Hyo-Jae Lee, Byung Chan Lee, Hyo Soon Lim, Yun-Hyeon Kim
Journal of Computer Assisted Tomography.2024; 48(3): 406. CrossRef
Interstitial Lung Abnormalities
Noriaki Wada, Gary M. Hunninghake, Hiroto Hatabu
Clinics in Chest Medicine.2024; 45(2): 433. CrossRef
Incidence and risk factors of pulmonary complications after lung cancer surgery: A systematic review and meta-analysis
Ting Deng, Jiamei Song, Jinmei Tuo, Yu Wang, Jin Li, Lorna Kwai Ping Suen, Yan Liang, Junliang Ma, Shaolin Chen
Heliyon.2024; 10(12): e32821. CrossRef
Survival impact of fibrotic interstitial lung abnormalities in resected stage IA non-small cell lung cancer
Won Gi Jeong, Yun-Hyeon Kim
The British Journal of Radiology.2023;[Epub] CrossRef
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Yoon Joo Shin, Jeong Geun Yi, Mi Young Kim, Donghee Son, Su Yeon Ahn
Journal of Clinical Medicine.2023; 12(21): 6858. CrossRef
Mycophenolate mofetil versus cyclophosphamide plus in patients with connective tissue disease-associated interstitial lung disease: Efficacy and safety analysis
Pengfei Wang, Li Zhang, Qian Guo, Lifen Zhao, Yanyan Hao
Open Medicine.2023;[Epub] CrossRef
Clinical implication of interstitial lung abnormality in elderly patients with early‐stage non‐small cell lung cancer
Seong Woo Cho, Won Gi Jeong, Jong Eun Lee, In‐Jae Oh, Sang Yun Song, Hye Mi Park, Hyo‐Jae Lee, Yun‐Hyeon Kim
Thoracic Cancer.2022; 13(7): 977. CrossRef

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Hematologic Malignancy

Prognostic Stratification of Patients with Burkitt Lymphoma Using Serum β2-microglobulin Levels: Hyung-Don Kim, Hyungwoo Cho, Shin Kim, Kyoungmin Lee, Eun Hee Kang, Jung Sun Park, Chan-Sik Park, Jooryung Huh, Jin Sook Ryu, Sang-Wook Lee, Dok-Hyun Yoon, Seok Jin Kim, Young Hyeh Ko, Won Seog Kim, Cheolwon Suh; Cancer Res Treat. 2021;53(3):847-856. Published online December 17, 2020; DOI: https://doi.org/10.4143/crt.2020.1060

Abstract PDF Supplementary Material PubReader ePub

Purpose
We aimed to investigate the prognostic value of serum β2-microglobulin for patients with Burkitt lymphoma (BL) and to propose a risk-stratifying classification system.
Materials and Methods
A prospective registry-based cohort study of BL patients treated with dose-intensive or effective dose-adjusted chemotherapies (n=81) was conducted. Survival outcomes were compared based on previously reported risk groups and/or serum β2-microglobulin levels. A risk-stratifying classification system incorporating serum β2-microglobulin levels was proposed and validated in an independent validation cohort (n=60).
Results
The median age was 47 years, and 57 patients (70.4%) were male. Patients with high serum β2-microglobulin levels (> 2 mg/L) had significantly worse progression-free survival (PFS) and overall survival (OS) (p < 0.01 for both). Serum β2-microglobulin levels further stratified patients in the low-risk and high-risk groups in terms of PFS (p=0.010 and p=0.044, respectively) and OS (p=0.014 and p=0.026, respectively). Multivariate analyses revealed that a high serum β2-microglobulin level (> 2 mg/L) was independently associated with a shorter PFS (hazards ratio [HR], 3.56; p=0.047) and OS (HR, 4.66; p=0.043). The new classification system incorporating the serum β2-microglobulin level allowed the stratification of patients into three distinct risk subgroups with 5-year OS rates of 100%, 89.5%, and 62.5%. In an independent cohort of BL, the system was validated by stratifying patients with different survival outcomes.
Conclusion
Serum β2-microglobulin level is an independent prognostic factor for BL patients. The proposed β2-microglobulin–based classification system could stratify patients with distinct survival outcomes, which may help define appropriate treatment approaches for individual patients.

Citations

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Ombretta Repetto, Filippo Sperti, Mariangela De Zorzi, Veronica Paduano, Stefano Realdon, Agostino Steffan, Renato Cannizzaro, Valli De Re
International Journal of Molecular Sciences.2026; 27(10): 4464. CrossRef
Predictors of survival among children with Burkitt lymphoma treated at a single center in Tanzania: a retrospective cohort study
Aika A. Shoo, Advera I. Ngazia, Nahya S. Masoud, Shakilu Jumanne, James J. Yahaya
Hematology, Transfusion and Cell Therapy.2026; 48(3): 106496. CrossRef
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Aythami de Armas‐Castellano, Diego Infante‐Ventura, Tasmania del Pino‐Sedeño, Yadira González Hernández, Raul Quiros, Beatriz León‐Salas, Vincent Ribrag, María M. Trujillo‐Martín
Cancer Medicine.2025;[Epub] CrossRef
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Xiangqun Zhang, Long Yang, Yu Gu, Junyuan Wu, Xue Mei, Shubin Guo
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