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Open research questions in Lung Cancer Diagnosis and Treatment

53 unresolved questions extracted from the limitations and future-work sections of 382 Lung Cancer Diagnosis and Treatment papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Our study, leveraging a large sample, offers a fresh perspective on the differences between these two groups—an approach not explored in previous research. The prognosis comparison between mucinous adeno- carcinoma and non-mucinous adenocarcinoma remains controversial among various studies [17–24].

    Radiological pure-solid appearance clinical stage I lung adenocarcinoma: a comparative study of mucinous and non-mucinous adenocarcinoma based on imaging features and survival outcomes · 2026 · DOI

  • BackgroundRobotic-assisted bronchoscopy combined with integrated cone-beam computed tomography (RAB+CBCT) enables accurate sampling of peripheral pulmonary lesions (PPLs), but the acquisition of diagnostic proficiency and program-level efficiency remains incompletely characterized.

    Learning Diagnostic Proficiency in Robotic-Assisted Bronchoscopy with Integrated Cone-Beam CT: A 680-Lesion Learning Curve Analysis · 2026 · DOI

  • While the processes underlying ICI resistance are not fully understood, some mechanisms influencing primary resistance, including tumor intrinsic factors (lack of tumor immunogenicity, loss of tumor antigen or HLA expression and aberrant signaling) and extrinsic factors (presence of immune suppressive cell populations, T cell exhaustion and upregulation of alternative immune checkpoints, and altered metabolism) have been described41,47-52 53-55. Distinct from prior reports, Several prior studies have identified key human TME components, such as tumor-infiltrating biomarkers of resistance and clinical outcome are lacking55.

    Patient-derived three-dimensional lung tumor models to evaluate response to therapy · 2026 · DOI

  • Such preoperative information may guide targeted intraoperative frozen-section sampling and support more cautious decisions regarding the extent of resection when frozen-section results are equivocal, thereby reducing the risk of inadequate margins due to underestimation of lesion invasiveness. This selection bias resulted in a higher proportion of malignant nodules than would be expected in a general screening population; therefore, the PPV reported in this study may be overestimated, and caution is warranted when generalizing conclusions to general outpatient screening popula- tions.

    Preoperative evaluation of solitary pulmonary nodules and adenocarcinoma invasiveness using ultra-high-resolution computed tomography and multidimensional liquid biopsy: a prospective exploratory study · 2026 · DOI

  • The UK National Screening Committee has recommended nationwide roll-out of LDCT screening, but the optimal risk thresholds for eligibility remain uncertain.

    Comparative cost-effectiveness of screening for lung cancer using different risk scores and thresholds: the Yorkshire Lung Screening Trial · 2026 · DOI

  • Tumor spread through airspaces (STAS) is a recognized pattern of aerogenous invasion; however, the potential role of biopsy-related hemorrhage in contributing to STAS-like dissemination remains uncertain.

    Iatrogenic Aerogenous Tumor Spread after CT-guided Lung Biopsy · 2026 · DOI

  • However, the optimal dose prescription method for SBRT remains controversial, with traditional isocenter-based prescriptions increasingly being replaced by volume-based prescriptions in clinical practice.

    Dosimetric and clinical outcomes of stereotactic body radiotherapy for primary lung cancer: isocenter-based vs. volume-based prescription · 2026 · DOI

  • CONCLUSIONS: PneumoScore demonstrated excellent performance for predicting 90-day mortality, a critical yet underexplored outcome in thoracic surgery, supporting its potential to enhance preoperative evaluation of patients with lung cancer.

    PneumoScore: Risk Prediction Model for 90-Day Mortality After Lung Resection · 2026 · DOI

  • RTOG) may make comparisons between studies unreliable; however, the low grades of toxicities reported in most cases do not raise a significant limitation [29]. Additional research is needed to establish standardized dosing pro- tocols, improve toxicity reporting, and explore SBRT’s role in more complicated and rare cases.

    The use of stereotactic radiotherapy in the treatment of lung malignancies — a scoping review · 2026 · DOI

  • Future work should address these gaps, while also exploring extensions that incorporate volumetric context (multi-slice or 3D representations) and more explicit uncertainty modeling, particularly for ambiguous cases near the benign–malignant boundary. choice keeps deployment At the same time, the present study is limited by the scope of the available data, and claims of clinical applicability must be carefully contextualized.

    Detection and classification of lung cancer using sequential hybridization of CNN and RNN type architectures · 2026 · DOI

  • Ping et al. (17) Multimodal IoMT-based fusion with Real-time diagnosis integrating imaging, Complex architecture; limited focus on federated learning and edge computing sensors, and EHR with privacy preservation spatial feature relationships Hassan et al.

    A spatial correlation-guided deep fusion framework for multimodal lung cancer classification using CT imaging · 2026 · DOI

  • Therefore, future research should focus on prospective study designs, standardized reporting in line with established guidelines, and rigorous external validation across diverse populations to strengthen clinical applicability. In addition, further work is needed to assess the real-world clinical impact of AI systems, including their effect on diagnostic pathways and patient outcomes, while also expanding applications toward biomarker quantification and multimodal data integration to advance precision lung cancer care.

    Evaluating the Accuracy of Artificial Intelligence Models for Early Lung Cancer Detection: Evidence From a Systematic Review · 2026 · DOI

  • Lung cancer research stands at a pivotal inflection point. Decades of work in genomics, immunology, and clinical investigation have revolutionized our understanding of lung cancer biology and delivered meaningful survival gains for subsets of patients. Advances in basic research, biotechnology, translational research, and data science offer tremendous opportunities to continue transforming patient care through early detection, prevention, and effective precision therapeutic interventions. Addressing critical knowledge gaps to develop a comprehensive understanding of disease mechanisms, overcome resistance to existing therapies, develop new interventions, advance clinical trials, and improve early detection and disease prevention requires concerted, interdisciplinary efforts. The AACR Lung Cancer Task Force is committed to spearheading these efforts, advocating for innovative funding models, and fostering collaborative research partnerships. Through these key initiatives, we aim not only to reduce lung cancer mortality, but also to achieve long-term disease control and move closer to a cure. ACKNOWLEDGMENTS D o w n l o a d e d f r o m h t t p: / / a a c r j o u r n a l s. o r g / c a n c e r d i s c o v e r y / a r t i c l e - p d f / d o i / 1 0. 1 1 5 8 / 2 1 5 9 - 8 2 9 0. C D - 2 5 - 2 3 1 8 / 3 7 7 5 0 3 9 / c d - 2 5 - 2 3 1 8. p d f b y g u e s t o n 2 0 A p r i l 2 0 2 6 25 The authors would like to thank Meina Wang (Yale Comprehensive Cancer Center, Yale University School of Medicine) and Carolina Salguero (University of Texas MD Anderson Cancer Center) for their assistance with Figures 1 and 3, respectively. AI was used only partially, specifically for generating some graphics in a few figures. The authors would also like to acknowledge other members of the AACR Lung Cancer Task Force for their expert input into this review; these members include Christopher Abbosh, Benjamin Bess, Trevor G. Bivona, Fiona H. Blackhall, Julie R. Brahmer, Iona C. Cheng, Dave Chuter, Harry J. De Koning, Maximilian Diehn, Caroline Dive, Susan M. Galbraith, Alena Gros, Mariam Jamal-Hanjani, Sam Janes, Pasi A. Jänne, Christopher A. Klebanoff, Se-Hoon Lee, Christine M. Lovly, Nicholas McGranahan, Tony S.K. Mok, Solange Peters, Kurt Schalper, Lecia V. Sequist, Alice T. Shaw, Lillian L. Siu, Benjamin J. Solomon, Avrum E. Spira, Brendon M. Stiles, Daniel S.W. Tan, Jennifer S. Temel, C. Jillian Tsai, Victor E. Velculescu, Everett E. Vokes, Johnathan R. Whetstine, Robert A. Winn, and James Chih-Hsin Yang. REFERENCES 1. 2. 3. 4. 5. 6. 7. 8. 9. Chhikara BS, Parang K. Global Cancer Statistics 2022: the trends projection analysis. Chemical Biology Letters. 2023;10:451.

    A Roadmap to Transform Lung Cancer Outcomes: Priorities in Biology, Therapeutic Innovation, Early Detection, Prevention and Interception · 2026 · DOI

  • The inconsistent use of different staging systems (AJCC vs IASLC classifications) across included studies introduced methodological inconsistency that may have confounded radiomics model performance in external validation cohorts; standardized staging system application should be established for future OLNM radiomics research.

    Diagnostic accuracy of CT-based radiomics for predicting occult lymph node metastasis in early-stage lung adenocarcinoma: a systematic review and meta-analysis · 2026 · DOI

  • Multi-center prospective validation studies with harmonized CT imaging protocols and standardized radiomics pipelines are required to establish reliable performance metrics for CT-based radiomics in OLNM prediction and to move beyond model development dataset-dependence that currently limits clinical translation.

    Diagnostic accuracy of CT-based radiomics for predicting occult lymph node metastasis in early-stage lung adenocarcinoma: a systematic review and meta-analysis · 2026 · DOI

  • Future research should develop and validate integrated radiomics approaches that combine CT-based radiomics parameters with conventional imaging parameters and clinical variables to determine optimal integration strategies for patient decision-making and selection of candidates for aggressive nodal evaluation.

    Diagnostic accuracy of CT-based radiomics for predicting occult lymph node metastasis in early-stage lung adenocarcinoma: a systematic review and meta-analysis · 2026 · DOI

  • The limited number of studies with external validation of CT-based radiomics models for OLNM restricted subgroup analyses and prevented definitive assessment of which radiomics model designs generalize best across different clinical stages (cT1 vs cT1-2) and tumor diameters (<2 cm vs ≥2 cm).

    Diagnostic accuracy of CT-based radiomics for predicting occult lymph node metastasis in early-stage lung adenocarcinoma: a systematic review and meta-analysis · 2026 · DOI

  • Substantial methodological heterogeneity existed across included studies in CT acquisition protocols, segmentation strategies, and radiomics pipelines for OLNM prediction; standardization of these technical parameters is needed before radiomics can be reliably applied in clinical practice for preoperative patient decision-making.

    Diagnostic accuracy of CT-based radiomics for predicting occult lymph node metastasis in early-stage lung adenocarcinoma: a systematic review and meta-analysis · 2026 · DOI

  • All included studies in this meta-analysis were retrospective and conducted exclusively in Asia, limiting generalizability of CT-based radiomics models for occult lymph node metastasis prediction to non-Asian populations and healthcare settings with different imaging infrastructure and patient demographics.

    Diagnostic accuracy of CT-based radiomics for predicting occult lymph node metastasis in early-stage lung adenocarcinoma: a systematic review and meta-analysis · 2026 · DOI

  • Future work should address these aspects to improve robustness, interpretability, and clinical applicability. Future work will focus on expanding to multi-institutional 3D datasets, exploring transformer- based and hybrid CNN–Transformer architectures, and incorporating quantitative XAI metrics for objective in- terpretability assessment.

    Lung cancer detection using Deep learning · 2026 · DOI

  • Although robust long-term survival data are still lacking, current findings suggest that RATS may represent a safe and effective option for mediastinal lymphadenectomy in NSCLC, particularly in centres with established robotic programs.

    Robot-assisted vs. video-assisted thoracoscopic surgery in the question of radicality of mediastinal lymphadenectomy · 2025 · DOI

  • BACKGROUND: There are limited data from randomized trials regarding whether volume-based, low-dose computed tomographic (CT) screening can reduce lung-cancer mortality among male former and current smokers.

    Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial · 2020 · DOI

  • CONCLUSION: Current evidence is insufficient to suggest a symptom profile for LC across the disease stages, nor can it be concluded that classical LC symptoms are predictors of LC apart from, perhaps, haemoptysis.

    A systematic review of symptomatic diagnosis of lung cancer · 2013 · DOI

  • However, applicability of these criteria in Asia remains uncertain, where many cases occur outside current criteria, including among persons with no smoking history.

    Screening Eligibility and Survival Among Patients With Lung Cancer in Korea · 2026 · DOI

  • However, because the available evidence is limited to a small number of retrospective studies with heterogeneous subgroup definitions and outcome reporting, ypN status should be regarded as a promising rather than validated postoperative prognostic factor.

    Prognostic significance of ypN status after neoadjuvant chemoimmunotherapy in resectable NSCLC: a systematic review and meta-analysis · 2026 · DOI

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53 open questions have been extracted from the limitations and future-work passages of 382 Lung Cancer Diagnosis and Treatment papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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