Hidetaka Uramoto

Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC), but disease progression during or after immunotherapy remains a major therapeutic challenge. ICI failure is biologically and clinically heterogeneous and may manifest as primary resistance, acquired resistance, oligoprogressive disease, hyperprogressive disease, or disease recurrence following treatment discontinuation. These distinct patterns may require different therapeutic approaches. In this review, we summarize the current evidence for treatment strategies after immunotherapy failure in advanced NSCLC. Cytotoxic chemotherapy remains a key subsequent-line treatment, though evidence supporting enhanced chemotherapy sensitivity after prior ICI exposure is largely derived from retrospective or non-randomized studies. Docetaxel plus ramucirumab is an established treatment option, but its specific efficacy after ICI failure has not been confirmed in randomized trials. Local therapies, including stereotactic body radiotherapy and salvage surgery, may provide meaningful local control in carefully selected patients with oligoprogressive or otherwise localized disease, though prospective evidence remains limited. ICI rechallenge generally has limited activity after progression during active ICI treatment, whereas re-exposure may be considered in selected patients after planned treatment completion or discontinuation because of immune-related adverse events. Biomarker development, including tissue biomarkers, circulating tumor DNA, circulating tumor cells, and emerging tumor–immune profiling approaches, may facilitate more individualized treatment selection. Overall, management after immunotherapy failure should be guided by the pattern and tempo of disease progression, prior treatment history, and the feasibility of systemic and local treatment. Further prospective studies are needed to establish effective treatment strategies and validated biomarkers for patient selection.

Background/Objectives: Published data on reliable prognostic biomarkers for pulmonary pleomorphic carcinoma (PPC), a rare, aggressive subtype of non-small cell lung cancer, are limited. Programmed death-ligand 1 (PD-L1) has been studied; however, the prognostic impact of other immunoregulatory molecules, such as CD73, CD155, and Ki-67 and their combined expression profiles, remains unclear. Methods: We retrospectively analyzed data of 47 patients who had undergone macroscopic complete resection of PPC between January 2000 and December 2022. Immunohistochemistry for PD-L1, CD73, CD155, and Ki-67 was performed. Cut-off values were determined by receiver operating characteristic analysis for cancer-specific death. The primary endpoint was the association between each biomarker and overall survival (OS) or cancer-specific survival (CSS). The secondary endpoint was the prognostic value of combined biomarker profiles, particularly PD-L1 with CD73, CD155, or Ki-67. Results: At a positivity threshold of 1%, the positivity rates were 70.2% for PD-L1, 89.4% for CD73, 91.5% for CD155, and 83.0% for Ki-67. There were no statistically significant differences in OS or CSS between groups with high expression and those with low expression for any single marker. Secondary endpoint analysis showed that low PD-L1 and low CD73 predicted significantly poorer OS (p = 0.046) and low PD-L1 and low Ki-67 predicted significantly poorer CSS (p = 0.039) compared with other combinations. Conclusions: Primary endpoint analyses showed no statistically significant association between any single marker and prognosis in PPC. In contrast, secondary endpoint findings indicated that concurrent low PD-L1 with either low CD73 or low Ki-67 identified subsets with significantly poorer outcomes. The present findings provide a basis for further investigation of biomarker combinations for prognostic assessment in this rare lung cancer. Because of the limited sample size, these findings are exploratory and require validation in larger independent cohorts.

Thin-slice high-resolution computed tomography (CT) has improved the detection of small pulmonary nodules, increasing the demand for minimally invasive diagnostic and therapeutic resection. While lobectomy with lymph node dissection remains the standard surgical approach for many patients with resectable non-small cell lung cancer, accumulating evidence supports sublobar resection for selected small, peripheral, and ground-glass-dominant lesions when sufficient margins are achievable. In thoracoscopic and robotic surgery, localization of nodules ≤10 mm or lesions located >5 mm from the pleural surface can be challenging, and failure to identify the target may lead to conversion, larger resection than intended, or prolonged operative time. Several localization strategies have been developed, including CT-guided percutaneous wire/coil/dye marking, bronchoscopic dye mapping, and virtual-assisted lung mapping (VAL-MAP), robotic-assisted bronchoscopic dye or fiducial localization, radiofrequency identification microtag systems (Surgical Real-Time FInger Navigation and Detection) that provide real-time depth information, and single-stage intraoperative CT-guided marking and resection in hybrid operating rooms. This review synthesizes representative evidence and published outcome ranges, and compares workflows, marker-to-lesion precision metrics, complication profiles, operational burden, and cost structures. We emphasize the practical contrast between two-stage and single-stage workflows, the access-route differences between transthoracic and transbronchial techniques, and the need to report localization-to-incision “time at risk”. We also present an expert-consensus decision algorithm aimed at facilitating tailored selection of localization strategies for modern minimally invasive thoracic surgery.