Small cell lung cancer: Subtypes and therapeutic implications

Comparison of the efficacy and safety of anlotinib monotherapy or anlotinib plus immune checkpoint inhibitor for advanced small cell lung cancer with brain metastases

BACKGROUND

Anlotinib, as a salvage treatment for patients after failure of third-line or later-line treatments for small cell lung cancer (SCLC), has shown efficacy in patients with brain metastases (BMs). However, the efficacy and safety of anlotinib alone or in combination with immunotherapy for SCLC with BMs remain unclear.

METHOD

Patients treated with anlotinib alone or in combination with an immune checkpoint inhibitor (ICI) at the Zhejiang Cancer Hospital between April 2019 and February 2023 were identified. Kaplan-Meier curves were used to describe the progression-free survival (PFS) and intracranial PFS (iPFS). A waterfall diagram was used to indicate changes in intracranial lesions.

RESULTS

A total of 48 patients were included; 29 received anlotinib alone, and 19 were administered anlotinib plus ICI. Combination therapy, compared with anlotinib, was associated with significantly longer PFS and iPFS (PFS: 8.1 months vs. 2.5 months, P < 0.001; iPFS: 8.1 months vs. 2.5 months, P = 0.004). Similar results were observed in patients with multiple BMs (PFS: 8.1 months vs. 1.9 months, P = 0.001; iPFS: 8.1 months vs. 1.9 months, P = 0.002). After third-line or later-line treatments, patients treated with ICI plus anlotinib also achieved significant PFS and iPFS benefits (PFS: 8.4 months vs. 2.1 months, P < 0.001; iPFS: 9.2 months vs. 2.1 months, P = 0.002). No new or severe adverse events were observed with combination therapy.

CONCLUSION

The combination of anlotinib and ICI has promising intracranial and extracranial efficacy with tolerable toxicity, and may be a therapeutic option for SCLC patients with BMs.

The rapidly changing field of predictive biomarkers of non-small cell lung cancer

Lung cancer is a leading cause of cancer-related death worldwide in both men and women, however mortality in the US and EU are recently declining in parallel with the gradual cut of smoking prevalence. Consequently, the relative frequency of adenocarcinoma increased while that of squamous and small cell carcinomas declined. During the last two decades a plethora of targeted drug therapies have appeared for the treatment of metastasizing non-small cell lung carcinomas (NSCLC). Personalized oncology aims to precisely match patients to treatments with the highest potential of success. Extensive research is done to introduce biomarkers which can predict the effectiveness of a specific targeted therapeutic approach. The EGFR signaling pathway includes several sufficient targets for the treatment of human cancers including NSCLC. Lung adenocarcinoma may harbor both activating and resistance mutations of the EGFR gene, and further, mutations of KRAS and BRAF oncogenes. Less frequent but targetable genetic alterations include ALK, ROS1, RET gene rearrangements, and various alterations of MET proto-oncogene. In addition, the importance of anti-tumor immunity and of tumor microenvironment has become evident recently. Accumulation of mutations generally trigger tumor specific immune defense, but immune protection may be upregulated as an aggressive feature. The blockade of immune checkpoints results in potential reactivation of tumor cell killing and induces significant tumor regression in various tumor types, such as lung carcinoma. Therapeutic responses to anti PD1-PD-L1 treatment may correlate with the expression of PD-L1 by tumor cells. Due to the wide range of diagnostic and predictive features in lung cancer a plenty of tests are required from a single small biopsy or cytology specimen, which is challenged by major issues of sample quantity and quality. Thus, the efficacy of biomarker testing should be warranted by standardized policy and optimal material usage. In this review we aim to discuss major targeted therapy-related biomarkers in NSCLC and testing possibilities comprehensively.

Zinc finger protein 367 exerts a cancer-promoting role in small cell lung cancer by influencing the CIT/LATS2/YAP signaling cascade

A remarkable cancer-related role of zinc finger protein 367 (ZNF367) has been demonstrated in multiple malignancies. However, whether ZNF367 has a role in small-cell lung cancer (SCLC) remains unexplored. The purpose of this work was to explore the potential role and mechanism of ZNF367 in SCLC. In silico analysis using the Gene Expression Omnibus (GEO) dataset revealed high levels of the ZNF367 transcript in SCLC. Examination of clinical tissues confirmed the significant abundance of ZNF367 in SCLC tissues compared with adjacent non-malignant tissues. The genetic depletion of ZNF367 in SCLC cells led to remarkable alterations in cell proliferation, the cell cycle, colony formation and chemosensitivity. Mechanistically, ZNF367 was shown to regulate the activation of yes-associated protein (YAP) associated with the up-regulation of phosphorylated large tumour suppressor kinase 2 (LATS2). Further investigation revealed that ZNF367 affected the LATS2-YAP cascade by regulating the expression of citron kinase (CIT). Re-expression of constitutively active YAP diminished the tumour-inhibiting function of ZNF367 depletion. Xenograft experiments confirmed the tumour-inhibiting effect of ZNF367 depletion in vivo. In summary, our results demonstrate that the inhibition of ZNF367 displays anticancer effects in SCLC by inhibiting YAP activation, suggesting it as a potential druggable oncogenic target.

Transitioning to a Personalized Approach in Molecularly Subtyped Small-Cell Lung Cancer (SCLC)

Lung cancer has become a major public health concern, standing as the leading cause of cancer-related deaths worldwide. Among its subtypes, small-cell lung cancer (SCLC) is characterized by aggressive and rapid growth, poor differentiation, and neuroendocrine features. Typically, SCLC is diagnosed at an advanced stage (extensive disease, ED-SCLC), with distant metastases, and is strongly associated with tobacco smoking and has a poor prognosis. Recent clinical trials, such as CASPIAN and IMpower133, have demonstrated promising outcomes with the incorporation of immune checkpoint inhibitors in first-line chemotherapy, leading to prolonged progression-free survival and overall survival in patients with ED-SCLC compared to standard chemotherapy. Other studies have emphasized the potential for future development of molecularly targeted therapies in SCLC patients, including inhibitors of IGF-1R, DLL3, BCL-2, MYC, or PARP. The molecular subdivision of SCLC based on transcriptomic and immunohistochemical analyses represents a significant advancement in both diagnostic and clinical approaches in SCLC patients. Specific molecular pathways are activated within distinct transcriptome subtypes of SCLC, offering the potential for personalized treatment strategies, such as targeted therapies and immunotherapies. Such tailored approaches hold promise for significantly improving outcomes in SCLC patients.

Immune Checkpoint Inhibitor-Associated Systemic Sclerosis in the Treatment of a Small Cell Lung Cancer Patient with Durvalumab: A Case Report

As one of the key cancer treatment measures, immune-checkpoint inhibitors (ICIs) have revolutionized the treatment landscape of various cancers, including malignancies previously thought to be untreatable. Immune checkpoint inhibitors work by targeting the dysfunctional immune system, to enhance cancer-cell killing by CD8-positive T cells. Despite the beneficial effects of ICIs, these treatments are also linked to a novel class of side effects, termed immune-related adverse events (irAEs). Immune-related adverse events can affect multiple organ systems, such as endocrine, neurological, gastroenteric, dermatologic, ocular, hepatic, renal, and rheumatic ones. While variable in severity, irAEs can be associated with significant morbidity, mortality, cessation of ICI treatment and can be potentially life-threatening sometimes. Among varieties of irAEs, dermatological manifestations are frequently reported, since they can be easily observed. Here, we present a case of a 74-year-old patient with widespread fibrosis of skin, eventually diagnosed as diffuse cutaneous systemic sclerosis after the treatment with durvalumab for small cell lung cancer (SCLC). Prompt recognition and treatment of immune-checkpoint inhibitors-associated systemic sclerosis may help enhance tolerance to ICIs and ensure better performance in treating tumors.

Synchronous double primary small cell lung cancer and invasive ductal breast carcinoma: a case report

BACKGROUND

Although lung and breast cancers are common malignancies, the occurrence of primary synchronous neoplasms involving these organs has been rarely reported in literature.

CASE PRESENTATION

A 75-year-old female patient presented at a local hospital with a ten-day history of dizziness and slurred speech. A CT contrast-enhanced scan revealed a 4.2 cm mass in the lower lobe of the right lung and a 3.8 cm space-occupying lesion in the right breast. Subsequent breast ultrasound identified a hypoechoic lesion measuring5.41 × 4.75 × 3.06 cm in the right breast, and an ultrasound-guided biopsy confirmed the presence of infiltrating ductal carcinoma of the right breast. The immunohistochemistry analysis of the breast mass revealed positive staining for ER, PR, HER-2, AR and Ki67 in the tumor cells, while negative staining was observed for P63, Calponin, CK5/6 and CK14. MR imaging of the head detected abnormal signals in the right frontal lobe (3.6 cm×2.9 cm in size), left cerebellar hemisphere, and punctate enhancement in the left temporal lobe, indicating potential metastasis. Pathological examination of a lung biopsy specimen confirmed the presence of small cell lung cancer (SCLC). Furthermore, immunohistochemistry analysis of the lung lesions demonstrated positive staining for TTF-1, CK-Pan, Syn, CgA, CD56, P53 (90%) and Ki67 (70%), and negative staining for NapsinA and P40 in the tumor cells. The patient's diagnosis of SCLC with stage cT2bN0M1c IVB and brain metastases (BM), as well as invasive ductal breast carcinoma (IDC), was confirmed based on the aforementioned results. Whereupon we proposed a treatment plan consisting of whole-brain radiation (40 Gy/20fractions), focal radiotherapy (60 Gy/20fractions), and adjuvant concurrent chemotherapy with oral etoposide (50 mg on days 1 to 20).

CONCLUSIONS

To the best of our knowledge, the present case is the first of its kind to describe the synchronous double cancer, consisting of primary SCLC and IDC.

Exosome inhibition improves response to first-line therapy in small cell lung cancer

Exosomes are recognized as important mediators of cell-to-cell communication, facilitating carcinogenesis. Although there have been significant advancements in exosome research in recent decades, no drugs that target the inhibition of sEV secretion have been approved for human use. For this study, we employed GW4869 and Nexinhib20 as inhibitors of exosome synthesis and trafficking combined. First, we found that Nexinhib20 and GW4869 effectively inhibited RAB27A and neutral sphingomyelinase 2 (nSMase2) nsMase2. Interestingly, the inhibition of nsMase2 and RAB27A decreased expression of CD9, CD63 and Tsg101, both at RNA and protein levels. We used a combination treatment strategy of cisplatin/etoposide plus GW4869 or Nexinhib20 on small cell lung cancer (SCLC) cell lines. The combination treatment of GW4869 or Nexinhib20 effectively enhanced the inhibitory effects of first-line chemotherapy on the SCLC cells. Furthermore, we demonstrated that reducing exosome release through GW4869 and Nexinhib20 treatment effectively reduced cellular proliferation and significantly induced apoptosis in SCLC cells. Also, we showed that combining exosome inhibition with chemotherapy has a significant synergistic effect on cellular proliferation. We also found increased p53 and p21 expressions with western blot and significantly changing Bax, BCL2, caspase-3 and caspase-9 expressions. Inhibiting the exosome pathway offers opportunities for developing novel, effective treatment strategies for SCLC.

The integration of multi-omics analysis and machine learning for the identification of prognostic assessment and immunotherapy efficacy through aging-associated genes in lung cancer

BACKGROUND

Recent years revealed key molecules in lung cancer research, yet their exact roles in disease onset and progression remain uncertain. Lung cancer's heterogeneity complicates prognosis prediction. This study integrates pivotal molecules to evaluate patient prognosis and immunotherapy efficacy.

METHODS

The WGCNA algorithm identified module genes linked to immunity. The Lasso-Cox method built a prognostic model for outcome prediction. GO and KEGG analyses explored gene pathways. ssGSEA quantified immune cell types and functions. The riskScore predicts the effectiveness of immunotherapy based on its correlation with DNA repair and immune checkpoint genes. Single-cell sequencing examined key gene expression across cell types.

RESULTS

Using WGCNA, we identified the MEbrown module related to immunity. Lasso-Cox selected "BLK," "ITGB4," "PRKCH," and "SNAI1" for the prognostic model. MF analysis revealed enriched functions including antigen binding, GTPase regulator activity. In terms of BP, processes like immune signaling and mitotic division were enriched. CC enrichment included immunoglobulin complexes and chromosomal regions. Enriched pathways encompassed Cell cycle, Focal adhesion, Cellular senescence, and p53 signaling. ssGSEA evaluated immune cell abundance. RiskScore correlated with CTLA4 and PD1 through MMR and immune checkpoint analysis. Single-cell analysis indicated gene expression across cell types for BLK, ITGB4, PRKCH, and SNAI1.

CONCLUSION

In summary, our developed prognostic model utilizing age-related genes effectively predicts lung cancer prognosis and the efficacy of immune therapy.

Single-cell RNA sequencing reveals immune microenvironment of small cell lung cancer-associated malignant pleural effusion

We used 10 × genomics single-cell transcriptome sequencing technology to reveal the tumor immune microenvironment characteristics of small cell lung cancer (SCLC) in a patient with malignant pleural effusion (MPE). A total of 8008 high-quality cells were finally obtained for subsequent bioinformatic analysis, which were divided into 10 cell clusters further identified as B cells, T cells, myeloid cells, NK cells, and cancer cells. Such SCLC related genes as NOTCH1, MYC, TSC22D1, SOX4, BLNK, YBX3, VIM, CD8A, CD8B, and KLF6 were expressed in different degrees during differentiation of T and B cells. Different ligands and receptors between T, B and tumor cells almost interact through MHC II, IL-16, galectin, and APP signaling pathway.

A plasma miRNA-based classifier for small cell lung cancer diagnosis

Introduction

Small cell lung cancer (SCLC) is characterized by poor prognosis and challenging diagnosis. Screening in high-risk smokers results in a reduction in lung cancer mortality, however, screening efforts are primarily focused on non-small cell lung cancer (NSCLC). SCLC diagnosis and surveillance remain significant challenges. The aberrant expression of circulating microRNAs (miRNAs/miRs) is reported in many tumors and can provide insights into the pathogenesis of tumor development and progression. Here, we conducted a comprehensive assessment of circulating miRNAs in SCLC with a goal of developing a miRNA-based classifier to assist in SCLC diagnoses.

Methods

We profiled deregulated circulating cell-free miRNAs in the plasma of SCLC patients. We tested selected miRNAs on a training cohort and created a classifier by integrating miRNA expression and patients' clinical data. Finally, we applied the classifier on a validation dataset.

Results

We determined that miR-375-3p can discriminate between SCLC and NSCLC patients, and between SCLC and Squamous Cell Carcinoma patients. Moreover, we found that a model comprising miR-375-3p, miR-320b, and miR-144-3p can be integrated with race and age to distinguish metastatic SCLC from a control group.

Discussion

This study proposes a miRNA-based biomarker classifier for SCLC that considers clinical demographics with specific cut offs to inform SCLC diagnosis.

Exploration of potential novel drug targets and biomarkers for small cell lung cancer by plasma proteome screening

Background: Small cell lung cancer (SCLC) is characterized by extreme invasiveness and lethality. There have been very few developments in its diagnosis and treatment over the past decades. It is urgently needed to explore potential novel biomarkers and drug targets for SCLC. Methods: Two-sample Mendelian Randomization (MR) was performed to investigate causal associations between SCLC and plasma proteins using genome-wide association studies (GWAS) summary statistics of SCLC from Transdisciplinary Research Into Cancer of the Lung Consortium (nCase = 2,791 vs. nControl = 20,580), and was validated in another cohort (nCase = 2,664 vs. nControl = 21,444). 734 plasma proteins and their genetic instruments of cis-acting protein quantitative trait loci (pQTL) were used, whereas external plasma proteome data was retrieved from deCODE database. Bidirectional MR, Steiger filtering and phenotype scanning were applied to further verify the associations. Results: Seven significant (p < 6.81 × 10-5) plasma protein-SCLC pairs were identified by MR analysis, including ACP5 (OR = 0.76, 95% CI: 0.67-0.86), CPB2 (OR = 0.90, 95% CI: 0.86-0.95), GSTM3 (OR = 0.45, 95% CI: 0.33-0.63), SHMT1 (OR = 0.74, 95% CI: 0.64-0.86), CTSB (OR = 0.79, 95% CI: 0.71-0.88), NTNG1 (OR = 0.81, 95% CI: 0.74-0.90) and FAM171B (OR = 1.40, 95% CI: 1.21-1.62). The external validation confirmed that CPB2, GSTM3 and NTNG1 had protective effects against SCLC, while FAM171B increased SCLC risk. However, the reverse causality analysis revealed that SCLC caused significant changes in plasma levels of most of these proteins, including decreases of ACP5, CPB2, GSTM3 and NTNG1, and the increase of FAM171B. Conclusion: This integrative analysis firstly suggested the causal associations between SCLC and plasma proteins, and the identified several proteins may be promising novel drug targets or biomarkers for SCLC.

Assessing treatment outcomes of chemoimmunotherapy in extensive-stage small cell lung cancer: an integrated clinical and radiomics approach

BACKGROUND

Small cell lung cancer (SCLC) is a highly malignant cancer characterized by metastasis and an extremely poor prognosis. Although combined chemoimmunotherapy improves the prognosis of extensive-stage (ES)-SCLC, the survival benefits remain limited. Furthermore, no reliable biomarker is available so far to predict the treatment outcomes for chemoimmunotherapy.

METHODS

This retrospective study included patients with ES-SCLC treated with first-line combined atezolizumab or durvalumab with standard chemotherapy between Janauray 1, 2019 and October 1, 2022 at five medical centers in China as the chemoimmunotherapy group. The patients were divided into one training cohort and two independent external validation cohorts. Additionally, we created a control group of ES-SCLC who was treated with first-line standard chemotherapy alone. The Radiomics Score was derived using machine learning algorithms based on the radiomics features extracted in the regions of interest delineated on the chest CT obtained before treatment. Cox proportional hazards regression analysis was performed to identify clinical features associated with therapeutic efficacy. The log-rank test, time-dependent receiver operating characteristic curve, and Concordance Index (C-index) were used to assess the effectiveness of the models.

RESULTS

A total of 341 patients (mean age, 62±8.7 years) were included in our study. After a median follow-up time of 12.1 months, the median progression-free survival (mPFS) was 7.1 (95% CI 6.6 to 7.7) months, whereas the median overall survival (mOS) was not reached. The TNM stage, Eastern Cooperative Oncology Group performance status, and Lung Immune Prognostic Index showed significant correlations with PFS. We proposed a predictive model based on eight radiomics features to determine the risk of chemoimmunotherapy resistance among patients with SCLC (validation set 1: mPFS, 12.0 m vs 5.0 m, C-index=0.634; validation set 2: mPFS, 10.8 m vs 6.1 m, C-index=0.617). By incorporating the clinical features associated with PFS into the radiomics model, the predictive efficacy was substantially improved. Consequently, the low-progression-risk group exhibited a significantly longer mPFS than the high-progression-risk group in both validation set 1 (mPFS, 12.8 m vs 4.5 m, HR=0.40, p=0.028) and validation set 2 (mPFS, 9.2 m vs 4.6 m, HR=0.30, p=0.012). External validation set 1 and set 2 yielded the highest 6-month area under the curve and C-index of 0.852 and 0.820, respectively. Importantly, the integrated prediction model also exhibited considerable differentiation power for survival outcomes. The HR for OS derived from the low-progression-risk and high-progression-risk groups was 0.28 (95% CI 0.17 to 0.48) in all patients and 0.20 (95% CI 0.08 to 0.54) in validation set. By contrast, no significant differences were observed in PFS and OS, between high-progression-risk patients receiving chemoimmunotherapy and the chemotherapy cohort (mPFS, 5.5 m vs 5.9 m, HR=0.90, p=0.547; mOS, 14.5 m vs 13.7 m, HR=0.97, p=0.910).

CONCLUSIONS

The integrated clinical and radiomics model can predict the treatment outcomes in patients with ES-SCLC receiving chemoimmunotherapy, rendering a convenient and low-cost prognostic model for decision-making regarding patient management.

Multi-dimensional characterization of immunological profiles in small cell lung cancer uncovers clinically relevant immune subtypes with distinct prognoses and therapeutic vulnerabilities

Small-cell lung cancer (SCLC) is generally considered a 'homogenous' disease, with little documented inter-tumor heterogeneity in treatment guidance or prognosis evaluation. The precise identification of clinically relevant molecular subtypes remains incomplete and their translation into clinical practice is limited. In this retrospective cohort study, we comprehensively characterized the immune microenvironment in SCLC by integrating transcriptional and protein profiling of formalin-fixation-and-paraffin-embedded (FFPE) samples from 29 patients. We identified two distinct disease subtypes: immune-enriched (IE-subtype) and immune-deprived (ID-subtype), displaying heterogeneity in immunological, biological, and clinical features. The IE-subtype was characterized by abundant immune infiltrate and elevated levels of interferon-alpha/gamma (IFNα/IFNγ) and inflammatory response, while the ID-subtype featured a complete lack of immune infiltration and a more proliferative phenotype. These two immune subtypes are associated with clinical benefits in SCLC patients treated with adjuvant therapy, with the IE-subtype exhibiting a more favorable response leading to improved survival and reduced disease recurrence risk. Additionally, we identified and validated a personalized prognosticator of immunophenotyping, the CCL5/CXCL9 chemokine index (CCI), using machine learning. The CCI demonstrated superior predictive abilities for prognosis and clinical benefits in SCLC patients, validated in our institute immunohistochemistry cohort and multicenter bulk transcriptomic data cohorts. In conclusion, our study provides a comprehensive and multi-dimensional characterization of the immune architecture of SCLC using clinical FFPE samples and proposes a new immune subtyping conceptual framework enabling risk stratification and the appropriate selection of individualized therapy.

Clinical relevance of stem cells in lung cancer

Lung cancer is the major cause of cancer-related deaths worldwide, it has one of the lowest 5-year survival rate, mainly because it is diagnosed in the late stage of the disease. Lung cancer is classified into two groups, small cell lung cancer (SCLC) and non-SCLC (NSCLC). In turn, NSCLC is categorized into three distinct cell subtypes: Adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. NSCLC is the most common lung cancer, accounting for 85% of all lung cancers. Treatment for lung cancer is linked to the cell type and stage of the disease, involving chemotherapy, radiation therapy, and surgery. Despite improvements in therapeutic treatments, lung cancer patients show high rates of recurrence, metastasis, and resistance to chemotherapy. Lung stem cells (SCs) are undifferentiated cells capable of self-renewal and proliferation, are resistant to chemotherapy and radiotherapy and, due to their properties, could be involved in the development and progression of lung cancer. The presence of SCs in the lung tissue could be the reason why lung cancer is difficult to treat. The identification of lung cancer stem cells biomarkers is of interest for precision medicine using new therapeutic agents directed against these cell populations. In this review, we present the current knowledge on lung SCs and discuss their functional role in the initiation and progression of lung cancer, as well as their role in tumor resistance to chemotherapy.

Comprehensive genetic analysis of histological components of combined small cell carcinoma

Background

Combined small‐cell lung cancer (cSCLC) is a rare type of small‐cell lung cancer (SCLC) that includes both SCLC and non‐small‐cell lung cancer (NSCLC). The molecular biological mechanisms underlying the heterogeneity of histological types in combined or metachronously transformed SCLC (mtSCLC) remain unclear. This study aimed to investigate the relationship between genetic alterations and each histological component heterogeneously detected in cSCLC and mtSCLC.

Methods

This study included four cSCLC cases and one mtSCLC case. Formalin‐fixed and paraffin‐embedded sections of each histological component of these tumors were subjected to next‐generation sequencing (NGS) and quantitative reverse transcription‐polymerase chain reaction to investigate the genetic mutations and expression levels of neuroendocrine cell‐specific transcription factors (achaete‐scute homolog‐1 [ASCL1], brain‐2 [BRN2] also known as POU domain class 3 transcription factor 2, nuclear factor 1 B [NF1B], insulinoma‐associated protein 1 [INSM1], and thyroid transcription factor‐1 [TTF‐1]).

Results

NGS analysis revealed that SCLC and NSCLC components share the same somatic mutations detected most frequently in TP53, and also in RB1 and EGFR. Gene expression analysis showed ASCL1 expression was significantly lower in the NSCLC component than in the SCLC component.

Conclusion

We conclude that the morphological evolution of heterogeneous histological components in cSCLC may be associated with differences in ASCL1 expression levels, but not in acquired somatic gene mutations.