Feasibility of two-step approach for screening NTRK fusion in two major subtypes of non-small cell lung cancer within a large cohort.

Our objective is to investigate a cost-effective approach to screen for NTRK fusion in the major subtypes of non-small cell lung cancer (NSCLC). Evaluate the concordance between immunohistochemistry (IHC) and next-generation sequencing (NGS), as well as between fluorescence in situ hybridization (FISH) and NGS, to detect any discrepancies in methodological consistency between lung adenocarcinoma (LADC) and lung squamous cell carcinoma (LSCC). Analyze the factors influencing IHC results. A cohort of 1654 patients with NSCLC underwent screening for NTRK fusion using whole slide IHC. The positive cases were analyzed by both FISH and NGS. Totally, 57 tested positive for pan-TRK, with positivity rates of 0.68% (10/1467) for LADC and 29.01% (47/162) for LSCC. FISH showed separate NTRK1 and NTRK3 rearrangements in two pan-TRK-positive LADCs, while all LSCCs tested negative. NGS confirmed functional NTRK fusion in two FISH-positive cases: one involving TPM3-NTRK1 and the other involving SQSTM1-NTRK3. A non-functional fusion of NTRK2-XRCC1 was detected in LSCC, while FISH was negative. According to our approach, the prevalence of NTRK fusion in NSCLC is 0.12%. The concordance rate between IHC and RNA-based NGS was 20% (2/10) in LADC and 0% (0/162) in LSCC. When the positive criteria increased over 50% of tumor cells showing strong staining, the concordance would be 100% (2/2). A concordance rate of 100% (2/2) was observed between FISH and RNA-based NGS in LADC. The expression of pan-TRK was significantly correlated with the tumor proportion score (TPS) of PD-L1 (p < 0.05) and transcript per million (TPM) values of NTRK2 (p < 0.05). We recommend using IHC with strict criteria to screen NTRK fusion in LADC rather than LSCC, confirmed by RNA-based NGS directly. When the NGS results are inconclusive, FISH validation is necessary.

Heterogeneity of molecular subtyping and therapy-related marker expression in primary tumors and paired lymph node metastases of small cell lung cancer.

The classification of molecular subtypes and the identification of targetable molecules have been proposed for small cell lung cancer (SCLC) patients. Our aim was to investigate whether the expression of these markers evaluated using lymph node (LN) metastases represents that of primary tumors. We enrolled 46 surgically resected SCLC patients' primary tumors and paired mediastinal LN metastases. The protein expression of subtype-defining markers (ASCL1, NEUROD1, POU2F3, and YAP1) and therapeutic markers (DLL3, MYC, PD-L1, and MHC I) was examined by immunohistochemistry and was correlated with clinicopathological parameters and prognoses. In primary and metastatic tumors, the expression of these markers was 78.3% and 87.0%, 50.0% and 63.0%, 13.0% and 6.5%, 17.4% and 15.2%, 84.8% and 87.0%, 17.4% and 6.5%, 50.0% and 34.8%, and 60.9% and 37.0%, respectively. Positive tumor PD-L1 expression was less present in LN metastases (p = 0.015), and the same was true for MHC I expression (p = 0.036). NEUROD1 and DLL3 expression levels in metastatic tumors were stronger (p < 0.001 and p = 0.002, respectively); conversely, POU2F3, MYC, PD-L1, and MHC I expression levels were weaker (p = 0.018, p = 0.019, p = 0.001, and p < 0.001, respectively). In 15 (32.6%) patients, we observed a change in the molecular subtyping pattern, and a higher number of neuroendocrine (NE)-high phenotype patients were diagnosed when using the LN specimens (91.3% vs. 84.8%). TNM stage and postoperative chemotherapy were independent prognostic factors in surgically resected SCLC patients, and no prognostic differences were found among molecular subtypes. This study highlights the discordance of subtype-specific proteins and therapeutic markers between SCLC primary tumors and LN metastases. Additionally, our findings have therapeutic and prognostic implications and warrant further clinical investigation.

Clonality Analysis for the Relationship between the Pulmonary Combined Neuroendocrine Carcinoma and "the So-Called Reported Histologic Transformation".

Histologic transformation (HT) is common following targeted therapy in adenocarcinoma. However, whether the transformed tumor is a new component or a combined neuroendocrine carcinoma (C-NEC) remains controversial. We aimed to explore the relationship between pulmonary C-NEC and HT. Macro-dissection was performed on different components of surgically resected C-NEC samples. Molecular alterations and clonal evolution were analyzed using whole exome sequencing (WES). The gene statuses for TP53 and RB1 were determined using immunohistochemistry (IHC) and WES to analyze the relationship between C-NEC and reported HT. Sixteen combined small-cell lung cancer patients and five combined large-cell neuroendocrine carcinoma patients were enrolled. The frequency of p53 and Rb inactivation, assessed using IHC in NEC and non-NEC components, was 76.2/76.2% and 66.7/61.9%, respectively. The expression consistency between the components was 81.0 and 85.7% for p53 and Rb, respectively. The frequencies of TP53, RB1, and EGFR mutations, assessed using WES in NEC and non-NEC components, were 81.0/81.0%, 28.6/28.6%, and 42.9/42.9%, respectively. The concordance rates for TP53, RB1, and EGFR were 90.5, 71.4, and 90.5%, respectively. The consistency rate between IHC and WES was 81.0 and 61.9% for TP53 and RB1, respectively. The different components had a common clonal origin for the 21 C-NECs in the clonal analysis, consistent with previous studies on HT. Our study shows that IHC is more sensitive for Rb detection and C-NEC, and the reported HT may be due to differences in evaluations between pathologist and clinicians. Assessing the p53/Rb and EGFR status for such cases would help in recognizing potential transformation cases or uncovering potential combined components.

Molecular subtypes, predictive markers and prognosis in small-cell lung carcinoma.

AIMS: A new molecular subtype classification was proposed for small-cell lung carcinoma (SCLC). We aimed to further validate the classification in various SCLC patient samples using immunohistochemistry (IHC) to highlight its clinical significance. METHODS: We analysed the protein expression of four subtype (achaete-scute family BHLH transcription factor 1 (ASCL1), neuronal differentiation 1 (NEUROD1), POU class 2 homeobox 3 (POU2F3) and Yes1-associated transcriptional regulator (YAP1)) and two predictive markers (delta-like ligand 3 (DLL3) and MYC) using IHC in 216 specimens from 195 SCLC patients, including 21 pairs of resected biopsy tumours. Associations among molecular subtypes, clinicopathological features and prognostic implications were also explored. RESULTS: The ASCL1, NEUROD1, POU2F3, YAP1, DLL3 and MYC-positive expression rates were 70.3%, 56.9%, 14.9%, 19.0%, 75.4% and 22.6%, respectively. DLL3 expression had positive and negative associations with that of ASCL1 and POU2F3/YAP1, respectively, whereas MYC had the opposite effect. Strong associations of ASCL1 (Ρ=0.8603, p<0.0001), NEUROD1 (Ρ=0.8326, p<0.0001), POU2F3 (Ρ=0.6950, p<0.0001) and YAP1 (Ρ=0.7466, p<0.0001) expressions were detected between paired resected biopsy tumours. In addition to SCLC-A (ASCL1-dominant), SCLC-N (NEUROD1-dominant) and SCLC-P (POU2F3-dominant), unsupervised hierarchical cluster analyses identified a fourth, quadruple-negative SCLC subtype (SCLC-QN) characterised by the low expression of all four subtype-specific proteins, and 55.4% (n=108), 27.2% (n=53), 11.8% (n=23) and 5.6% (n=11) were categorised as SCLC-A, SCLC-N, SCLC-P and SCLC-QN, respectively. Significant enrichment of SCLC-P in the combined SCLC cohort was observed, and adenocarcinoma was more prevalent in SCLC-A, while large-cell neuroendocrine carcinoma was more commonly seen in SCLC-P. No survival difference was found among molecular subtypes. CONCLUSIONS: Our results provide clinical insights into the diagnostic, prognostic and predictive significance of SCLC molecular subtype classifications.

Exploring the molecular features and genetic prognostic factors of pulmonary high-grade neuroendocrine carcinomas.

Molecular research on large-cell neuroendocrine carcinoma (LCNEC) and small-cell lung cancer (SCLC) has progressed significantly. However, there are still fewer molecular markers related to prognostic/therapeutic strategies for these conditions compared to those for adenocarcinoma. We therefore investigated the molecular characteristics of neuroendocrine carcinomas (NECs). We enrolled patients surgically diagnosed with NECs between 2011 and 2019, with complete follow-up records. All were analyzed using whole exome sequencing and p53/Rb immunohistochemistry (IHC). A total of 92 cases, comprising 45 pure SCLC, 15 combined SCLC, 27 pure LCNEC, and 5 combined LCNEC, were included. TP53 (78.3%) and RB1 (34.8%) were the most common molecular alterations, followed by KMT2D, LRP1B, FAT3, NCOR2, SPTA1, and NOTCH1. The mutation frequency for EGFR was 10.9%. Sixteen patients with LCNEC who had TP53/RB1 co-alterations were SCLC-like, while the remaining were NSCLC-like. There was no statistically significant difference between the groups regarding overall survival (OS; p = 0.458) and progression-free survival (PFS; p = 0.157). The frequency of the loss of Rb expression by IHC in SCLC-like LCNEC was 100%. Significant pathway alterations unique to SCLC included Notch and AMPK, while HIF-1 was enriched exclusively in LCNEC. NCOR2 mutation was linked to worse OS (p = 0.029) and PFS (p = 0.015), while wild-type SPTA1 was associated with poor PFS (p = 0.018). IHC for Rb was reliable for predicting LCNEC molecular subtypes, indicating its clinical value. NCOR2 and SPTA1 alterations were identified as prognostic factors that may provide therapeutic targets for patients with NEC.

Molecular subtype expression and genomic profiling differ between surgically resected pure and combined small cell lung carcinoma.

A new molecular subtype classification method has been proposed for small cell lung carcinoma (SCLC). However, little is known about the differences between the pure (P-SCLC) and combined subtypes (C-SCLC). We aimed to compare the molecular subtype expression and genomic profiling in terms of clinical relevance between the two groups. 154 surgically resected SCLCs were analyzed for protein expression of four subtypes (ASCL1, NEUROD1, POU2F3, and YAP1) and two predictive markers (DLL3 and MYC) by immunohistochemistry (IHC). We also performed whole exome sequencing of 60 samples to examine genomic profiles. A total of 113 patients with P-SCLC and 41 with C-SCLC were included. In P-SCLC and C-SCLC, the expression of these markers was 78.8% and 41.5%, 98.2% and 97.6%, 42.5% and 51.2%, 38.9% and 85.4%, 85.0% and 68.3%, and 24.8% and 34.1%, respectively. ASCL1 and DLL3 were highly expressed in P-SCLC (p = 0.000 and p = 0.021, respectively), and YAP1 expression was significantly enriched in C-SCLC (p = 0.000). NGS results, including 45 P-SCLCs and 15 C-SCLCs, indicated that EGFR gene mutations were mostly observed in C-SCLCs (p = 0.000). C-SCLC showed higher CNA burden and wGII than P-SCLC (p < 0.01 and p < 0.05); conversely, P-SCLC had higher TMB burden and SDI (p < 0.05 and p < 0.05). YAP1 expression was associated with poor prognosis in P-SCLC but with favorable prognosis in C-SCLC. P-SCLC and C-SCLC are heterogeneous diseases characterized by different molecular subtype expressions and genomic profiles. Our data provide a basis for adopting histological subtype-based treatments, and further prospective studies are required to confirm our conclusions.

Prognostic Value of Chromatin Structure Typing in Early-Stage Non-Small Cell Lung Cancer.

(1) Background: Chromatin structure typing has been used for prognostic risk stratification among cancer survivors. This study aimed to ascertain the prognostic values of ploidy, nucleotyping, and tumor-stroma ratio (TSR) in predicting disease progression for patients with early-stage non-small cell lung cancer (NSCLC), and to explore whether patients with different nucleotyping profiles can benefit from adjuvant chemotherapy. (2) Methods: DNA ploidy, nucleotyping, and TSR were measured by chromatin structure typing analysis (Matrix Analyser, Room4, Kent, UK). Cox proportional hazard regression models were used to assess the relationships of DNA ploidy, nucleotyping, and TSR with a 5-year disease-free survival (DFS). (3) Results: among 154 early-stage NSCLC patients, 102 were non-diploid, 40 had chromatin heterogeneity, and 126 had a low stroma fraction, respectively. Univariable analysis suggested that non-diploidy was associated with a significantly lower 5-year DFS rate. After combining DNA ploidy and nucleotyping for risk stratification and adjusting for potential confounders, the DNA ploidy and nucleotyping (PN) high-risk group and PN medium-risk group had a 4- (95% CI: 1.497-8.754) and 3-fold (95% CI: 1.196-6.380) increase in the risk of disease progression or mortality within 5 years of follow-up, respectively, compared to the PN low-risk group. In PN high-risk patients, adjuvant therapy was associated with a significantly improved 5-year DFS (HR = 0.214, 95% CI: 0.048-0.957, p = 0.027). (4) Conclusions: the non-diploid DNA status and the combination of ploidy and nucleotyping can be useful prognostic indicators to predict long-term outcomes in early-stage NSCLC patients. Additionally, NSCLC patients with non-diploidy and chromatin homogenous status may benefit from adjuvant therapy.

A prognostic classification based on the International Association for the Study of Lung Cancer histologic grading and immunoscore in KRAS-mutant invasive non-mucinous adenocarcinoma.

BACKGROUND: Tumor immune cell infiltration is important in the prognosis of patients with lung adenocarcinoma. The aim of this study was to develop a prognostic classification based on the tumor immunoscore. METHODS: Patients with KRAS-mutant invasive non-mucinous lung adenocarcinoma who underwent radical surgery were enrolled in the study. Histologic grading was assessed according to the recommendations of the International Association for the Study of Lung Cancer. Programmed death-ligand 1 (PD-L1) and CD8 expression was detected using immunohistochemistry. The number of CD8+ tumor-infiltrating lymphocytes (TILs) per high-power field was assessed. A classification based on histological grade and CD8+ TIL level was established (Grading-Immunoscore type): low-to-medium grade with high or low infiltration (type A); high-grade, high-infiltration (type B); and high-grade, low-infiltration (type C). RESULTS: A total of 112 patients participated. In the multivariable analysis, histological grading and level of CD8+ TILs were independent prognostic factors for overall survival (OS) and progression-free survival (PFS) (p < 0.001 and p = 0.007, respectively). Patients with type A tumors had the best OS and PFS, whereas those with type C tumors had the worst OS (89.6%, 65.0%, and 29.5% 5-year OS for types A, B, and C, respectively). PD-L1 positivity and high expression rate was highest in type B tumors (tumor proportion score [TPS] ≥ 1%: 29.4%, 73.1%, and 42.9%; TPS ≥50%: 7.8%, 42.3%, and 17.1%, for types A, B, and C, respectively). CONCLUSIONS: The Grading-Immunoscore classification refines the prognostic grouping of histological grading and might aid in the screening of potential candidates for immunotherapy in patients with KRAS-mutant adenocarcinoma.

Artificial intelligence-assisted system for precision diagnosis of PD-L1 expression in non-small cell lung cancer.

Standardized programmed death-ligand 1 (PD-L1) assessment in non-small cell lung cancer (NSCLC) is challenging, owing to inter-observer variability among pathologists and the use of different antibodies. There is a strong demand for the development of an artificial intelligence (AI) system to obtain high-precision scores of PD-L1 expression in clinical diagnostic scenarios. We developed an AI system using whole slide images (WSIs) of the 22c3 assay to automatically assess the tumor proportion score (TPS) of PD-L1 expression based on a deep learning (DL) model of tumor detection. Tests were performed to show the diagnostic ability of the AI system in the 22c3 assay to assist pathologists and the reliability of the application in the SP263 assay. A robust high-performance DL model for automated tumor detection was devised with an accuracy and specificity of 0.9326 and 0.9641, respectively, and a concrete TPS value was obtained after tumor cell segmentation. The TPS comparison test in the 22c3 assay showed strong consistency between the TPS calculated with the AI system and trained pathologists (R = 0.9429-0.9458). AI-assisted diagnosis test confirmed that the repeatability and efficiency of untrained pathologists could be improved using the AI system. The Ventana PD-L1 (SP263) assay showed high consistency in TPS calculations between the AI system and pathologists (R = 0.9787). In conclusion, a high-precision AI system is proposed for the automated TPS assessment of PD-L1 expression in the 22c3 and SP263 assays in NSCLC. Our study also indicates the benefits of using an AI-assisted system to improve diagnostic repeatability and efficiency for pathologists.

Validation of multiplex immunofluorescence and digital image analysis for programmed death-ligand 1 expression and immune cell assessment in non-small cell lung cancer: comparison with conventional immunohistochemistry.

AIMS: This study aimed to validate the application of combined multiplex immunofluorescence (mIF) and digital image analysis (DIA) in formalin-fixed and paraffin-embedded tissues for the quantitative assessment of programmed death-ligand 1(PD-L1) and immune cells (ICs) in non-small cell lung cancer (NSCLC). METHODS: Fifty resected samples of NSCLC were sequentially stained with a DNA-tagged mIF (panel including PD-L1, CKpan, CD8, CD68 and 4',6-diamidino-2-phenylindole (DAPI)) and conventional immunohistochemistry (cIHC). The assessment of cell density and consistency of tumour proportion score (TPS) via DIA were compared with those by pathologists. RESULTS: A strong correlation in the cell population of immune markers was obtained between mIF and cIHC (for PD-L1: R=0.9304, CKpan: R=0.8231, CD8: R=0.9314 and CD68: R=0.8366) within 95% limits of agreement. The continuous TPS calculated using mIF was highly consistent with the IHC staining results which were evaluated by pathologists (R=0.9362). However, in the comparison of TPS using interval variables, a poor agreement was obtained at a cut-off of 1% (κ=0.197), whereas excellent agreement was achieved at cut-offs of 50% (κ=0.908) and 5% (κ=0.823). DIA on mIF showed that PD-L1 commonly colocalised with CD68+ macrophages and CD8+ cytotoxic cells were closer to PD-L1-/CK+ tumour cells (TCs) than to PD-L1+/CK+ TCs in spatial distribution. CONCLUSIONS: A combination of mIF and DIA is useful for the quantification of PD-L1 expression and IC populations in NSCLC. Further validation of TPS at a cut-off of 1% and assay harmonisation is essential for translating this method in a diagnostic setting.

Heterogeneity of programmed death-ligand 1 expression and infiltrating lymphocytes in paired resected primary and metastatic non-small cell lung cancer.

Metastatic tumors (MTs) may show different characteristics of the immune microenvironment from primary tumors (PTs) in non-small cell lung cancer (NSCLC). The heterogeneity of immune markers in metastatic NSCLC and its associated factors has not been well demonstrated. In this study, 64 surgically resected specimens of paired PTs and MTs were obtained from 28 patients with NSCLC. Multiplex immunofluorescence (mIF; panel including programmed death-ligand 1 (PD-L1), Cytokeratin, CD8, and CD68) was performed on whole sections. The heterogeneity of the immune contexture of PD-L1 expression, infiltrating lymphocytes, and immune-to-tumor cell distances was quantified via digital image analysis. In a quantitative comparison of MTs and corresponding PTs, MTs showed higher PD-L1 expression levels, lower density of CD8+ cytotoxic T lymphocytes (CTLs), and longer spatial distance between CTLs and tumor cells. Subgroup analysis, which associated clinical factors, revealed that the heterogeneity of immune markers was more obvious in extrapulmonary, metachronous, and treated MTs, while fewer differences were observed in intrapulmonary, synchronous, and untreated MTs. In particular, MTs showed significantly higher PD-L1 expression and lower lymphocyte infiltration in metastatic NSCLC with EGFR mutations. Prognosis analysis showed that an increased density of CD8+ CTLs in MTs was associated with better overall survival (OS). Therefore, significant discrepancies in PD-L1 expression and lymphocyte infiltration in metastatic NSCLC are most likely associated with temporal heterogeneity with a history of anti-treatment and correlated with EGFR mutations. The detection of immune markers in re-obtained metastatic specimens may be required for immunotherapy prediction in these patients with metastatic NSCLC.

Major pathologic response assessment and clinical significance of metastatic lymph nodes after neoadjuvant therapy for non-small cell lung cancer.

For neoadjuvant therapy in patients with non-small cell lung cancer, the major pathologic response of primary tumors may be an assessable and reliable surrogate measure of survival. Few studies have examined the pathologic evaluation of metastatic lymph node responses and their prognostic significance. This retrospective study enrolled 336 patients with non-small cell lung cancer (squamous cell carcinoma, n = 216; adenocarcinoma, n = 120) treated with neoadjuvant therapy including chemotherapy (n = 316) and targeted therapy (adenocarcinoma, n = 20). The treatment response of the primary tumor and lymph node metastases (LNM) were pathologically assessed according to the multidisciplinary recommendations of the International Association for the Study of Lung Cancer. The relationship of overall survival (OS) and disease-free survival (DFS) with the responses of the primary tumor or LNM was analyzed. The optimal cutoff value of the residual viable tumor (%RVT) of the primary tumor was 12% for both OS (P < 0.001) and DFS (P < 0.001). The pathologic assessment identified LNM in 208 patients. The optimal %RVT cutoff value in LNM was 8% for both OS (P = 0.003) and DFS (P < 0.001). The Spearman's rank correlation coefficient between primary tumors and corresponding LNM was 0.487 for %RVT (P < 0.001), which indicated a positive correlation. On multivariable analysis, an RVT of the primary tumor ≤12% was an independent prognostic factor for improved OS (P = 0.024), whereas an RVT of LNM ≤ 8% was an independent prognostic factor for increased DFS (P = 0.018). Furthermore, in the neoadjuvant chemotherapy group, the optimal %RVT cutoff values for OS in patients with squamous cell carcinoma and adenocarcinoma in the primary tumor were 12% and 58%, respectively. Considering its convenience and operability in clinical application, a 10% threshold RVT value can be used for prognostic evaluation of LNM and primary tumors of squamous cell carcinoma histology; further studies are needed to confirm the optimal cutoff value for primary tumors of adenocarcinoma.

Knockdown of TM9SF4 boosts ER stress to trigger cell death of chemoresistant breast cancer cells.

Drug resistance is one of the major obstacles to breast cancer therapy. However, the mechanisms of how cancer cells develop chemoresistance are still not fully understood. In the present study, we found that expression of TM9SF4 proteins was much higher in adriamycin (ADM)-resistant breast cancer cells MCF-7/ADM than in its parental line wild-type breast cancer cells MCF-7/WT. shRNA-mediated knockdown of TM9SF4 preferentially reduced cell growth and triggered cell death in chemoresistant MCF-7/ADM cells compared with MCF-7/WT cells. Knockdown of TM9SF4 also reduced cell growth and triggered cell death in chemoresistant MDA-MB-231/GEM cells. Mechanistic studies showed that TM9SF4 knockdown increased protein misfolding and elevated endoplasmic reticulum (ER) stress level in MCF-7/ADM cells, as indicated by aggresome formation and upregulated expression of ER stress markers, the effect of which was reversed by a small molecule chaperone 4-phenybutyric acid. In an athymic nude mouse model of ADM-resistant human breast xenograft tumor, knockdown of TM9SF4 decreased the growth of tumor xenografts. In chemoresistant breast cancer patients, chemotherapy increased the expression of TM9SF4 proteins in breast tumor samples. Taken together, these results uncovered a novel role of TM9SF4 proteins in alleviating ER stress and protecting chemoresistant breast cancer cells from apoptotic/necrotic cell death. These results highlight a possible strategy of targeting TM9SF4 to overcome breast cancer chemoresistance.