新辅助化疗加安洛替尼治疗可切除的头颈部鳞状细胞癌:一项II期试验。

IF 24.9 1区 医学 Q1 ONCOLOGY
Qianting He, Shuojin Huang, Dongxiao Tang, Congyuan Cao, Wanhang Zhou, Rongsong Ling, Jie Chen, Bokai Yun, Xin Zheng, Yanchen Li, Anxun Wang, Demeng Chen
{"title":"新辅助化疗加安洛替尼治疗可切除的头颈部鳞状细胞癌:一项II期试验。","authors":"Qianting He,&nbsp;Shuojin Huang,&nbsp;Dongxiao Tang,&nbsp;Congyuan Cao,&nbsp;Wanhang Zhou,&nbsp;Rongsong Ling,&nbsp;Jie Chen,&nbsp;Bokai Yun,&nbsp;Xin Zheng,&nbsp;Yanchen Li,&nbsp;Anxun Wang,&nbsp;Demeng Chen","doi":"10.1002/cac2.70006","DOIUrl":null,"url":null,"abstract":"<p>Head and neck squamous cell carcinoma (HNSCC) continues to be a major global health challenge, with limited survival improvements for patients with locally advanced (LA) or recurrent (R) disease [<span>1</span>]. Anlotinib, a novel orally administered small-molecule tyrosine kinase inhibitor (TKI) developed in China, targets a wide range of receptor tyrosine kinases (RTKs) [<span>2</span>]. Our previous studies have also manifested that anlotinib remarkably inhibited the proliferation of HNSCC cells both in vitro and in vivo, and presented promising clinical antitumor efficacy and tolerable safety profile in patients with oral squamous cell carcinoma (OSCC) [<span>3, 4</span>]. This prospective trial was designed to evaluate the clinical efficacy and safety of anlotinib combined with paclitaxel and cisplatin (TP) neoadjuvant therapy in patients with resectable HNSCC. Additionally, the mechanisms underlying the effects of anlotinib and neoadjuvant chemotherapy on HNSCC were investigated through spatial transcriptomics (STs) and multiplex immunohistochemistry (mIHC).</p><p>Between October 2022 and May 2023, 20 resectable HNSCC patients were enrolled (median age, 55; range, 27-73). Baseline demographics and disease characteristics are detailed in Supplementary Tables S1-S2. All patients received 3 cycles of neoadjuvant therapy, followed by surgery in 17 and maintenance therapy in 16. No patients were lost to follow-up (study flowchart in Figure 1A). After neoadjuvant therapy, 95.0% (19/20) achieved partial response (PR), and 5.0% (1/20) achieved complete response (CR), with an Objective response rate (ORR) of 100% (95% confidence interval [CI], 83.2-100). Figure 1B shows the waterfall plot of tumor size changes. Surgical resection was performed in 17 patients (LA, 12; R, 5) with a 100% R0 resection rate, one patient declined surgery due to financial constraints and the other two did not want to perform surgery as their tumors had almost regressed. Postoperative pathological efficacy (Supplementary Table S3) showed pathological complete response (pCR) and major pathological response (MPR) in 7 patients each (41.2%; 95% CI, 18.4-67.1). Among 11 with positive cervical lymph nodes, 6 achieved pCR (54.5%; 95% CI, 23.4-83.3). Imaging and pathological data of patient #14 with CR are shown in Figure 1C-D.</p><p>All patients were followed for at least one year. Treatment responses and durations are shown in Figure 1E. By May 15, 2024, 17 out of 20 patients were alive. Of the 3 deaths, 1 patient with LA declined further therapy for financial constraints after neoadjuvant treatment and died a year later, another patient with LA refused maintenance therapy after surgery and died within a year, while one patient with LA died in a traffic accident four months post-radiotherapy. Among the all 20 patients, 5 (4 with LA and 1 with R) experienced local recurrence within 1 year. Of the 17 patients with R0 resection, 4 (3 with LA and 1 with R) had a local recurrence within 1 year.</p><p>Treatment Emergent Adverse Events (TEAEs) are summarized in Supplementary Tables S4-S5. All patients experienced at least one TEAE post-neoadjuvant therapy, primarily grades 1-2. Common TEAEs included alopecia (100%), hypertension (90%), anemia (85%), and hand-foot syndrome (45%). Grade 3 TEAEs occurred in 50% of patients. No TRAEs caused drug discontinuation, dose reduction, death, or surgical delays.</p><p>To investigate the effects of neoadjuvant therapy on HNSCC, STs were conducted using Formalin Fixed Paraffin Embedded (FFPE) samples from 4 pCR and 3 non-pCR patients (Figure 1F, Supplementary Table S6). All 48,666 capture spots passed quality control, yielding a mean of 15,016 reads per spot (52.2 million per capture) and 4,498 mapped genes per sample.</p><p>Unsupervised clustering using the Louvain algorithm identified 10 niches across 14 samples (Supplementary Figure S1A), present in varying proportions (Supplementary Figure S1B). Each spot, containing 1-10 cells, was analyzed via multimodal intersection analysis (MIA) [<span>5</span>] with Single-cell RNA sequencing (scRNA-seq) datasets (GSE234933 and GSE181919). MIA predicted high malignant cell incidence in Niches 1, 4, and 6; Cancer Associated Fibroblasts (CAFs) in Niche 2; B cells and CAFs in Niche 3; endothelial cells and CAFs in Niches 5 and 7; immune cells in Niches 8 and 10; and ambiguous markers in Niche 9 (Supplementary Figure S1C). Manual annotation with cell type markers confirmed MIA results (Supplementary Figure S1D). Copy Number Variation (CNV) analysis showed recurrent chromosome 1 deletions and chromosome 3 amplifications in Niches 1, 4, and 6, aligning with prior studies [<span>6</span>]. Some Niche 1 spots exhibited low CNV, suggesting non-malignant squamous epithelial cells (Supplementary Figure S1E-F). Mapping niches onto FFPE sections revealed tumor regions comprised Niches 1, 4, and 6, with distinct spatial distributions: in addition to posttreatment samples of pCR patients, Niche 6 is primarily located at the tumor periphery, Niche 1 at the intermediate epithelial region, and Niche 4 at the leading edge. (Supplementary Figure S2). Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) analysis inferred tumor, stromal, and immune substructures, closely matching histological annotations (Supplementary Figure S3). Non-negative matrix factorization (NMF) [<span>7</span>] identified 11 transcriptional metaprograms, including a recurrent part Epithelial-Mesenchymal Transition (pEMT) module (COL17A1, LAMA3, and LAMC2), stress response genes (S100A9, S100A8, and KRT6A), and hypoxia-response genes (ENO1, DDIT4, and VEGFA; Supplementary Figure S4A-B. Other programs corresponded to CAF (ECM-CAFs: COL1A1, COL1A2, and COL3A1; myo-CAFs: DES, ACTN2, and MYH2) and immune lineages. NMF results aligned with niche classifications (Supplementary Figure S4C-D).</p><p>To further examine treatment effects on HNSCC, we analyzed niche compositions before and after treatment. Posttreatment samples showed significant decreases in Niche 4 and Niche 6 (Niche 4: 23.9% to 2.8%; Niche 6: 13.4% to 5.2%), reflecting a robust anti-tumor effect (Supplementary Figure S5A). Conversely, Niche 3, 5, 7, and 8 increased posttreatments (Niche 3: 6.9% to 16.9%; Niche 5: 7.6% to 13.4%; Niche 7: 4.7% to 7.3%; Niche 8: 2.1% to 8.3%). Gene Set Variation Analysis (GSVA) analysis revealed upregulated mRNAs in posttreatment samples enriched in pathways related to B cell receptor signaling, complement action, and adaptive immune response, while downregulated mRNAs were linked to epidermis development and cell cycle regulation (Supplementary Figure S5B). Niche 3, primarily composed of B cells and CAFs (Supplementary Figure S1C), was located near tumor niches (Supplementary Figure S2), suggesting interactions with tumor cells. Transcriptomic analysis showed that pretreatment Niche 3 was associated with extracellular matrix (ECM) markers (e.g., COL7A1 and DSP), while posttreatment samples displayed upregulation of immune regulatory genes and B cell activation markers (e.g., IGHG3, IGLC1, SFRP2, and SFPR4; Supplementary Figure S5C). Gene Set Enrichment Analysis (GSEA) confirmed enrichment of immune response and B cell-mediated immunity gene sets in posttreatment Niche 3 (Supplementary Figure S5D). CellChat analysis revealed increased communication strength between Niche 3 and tumor niches (Niche 1, 4, and 6) after treatment (Supplementary Figure S5E-F). Ligand-receptor pairs (C3-ITGAX + ITGB2, CCL5-ACKR1, and SEMA3C-PLXND1) were significantly upregulated posttreatment, suggesting their role in anti-tumor immunity (Supplementary Figure S5G). Flow pattern showed dominant SEMA3, CCL, ANGPTL, and COMPLEMENT signaling pathways posttreatment, whereas VEGFA, VISFATIN, NRG, and ncWNT were predominant pretreatment (Supplementary Figure S5H).</p><p>To delineate key molecular characteristics of non-pCR samples, we manually selected spots from residual tumors (Supplementary Figure S6A) and identified an insensitive signature score via Differential Expression Gene (DEG) analysis between residual tumor cells and other niches (Supplementary Figure S6B-C). GSEA revealed upregulated genes enriched in pathways, such as oxidative phosphorylation, MYC targets, DNA repair, and interferon alpha response (Supplementary Figure S6D-E). Using high-dimensional Weighted Gene Co-expression Network Analysis (hdWGCNA), we identified seven gene modules, with Module RN4 showing the highest positive correlation to the insensitive score (Supplementary Figure S6F-H). Python-based Single-Cell Regulatory Network Inference and Clustering (PySCENIC) analysis revealed differentially activated transcription factors (TFs), including HES1, FOXQ1, and FOXA1, in the insensitive niche (Supplementary Figure S6I).</p><p>Notably, FOXQ1 was consistently identified across datasets and was significantly enriched in naïve non-pCR samples compared to naïve pCR samples, suggesting its key role in tumor cell insensitivity (Supplementary Figure S7A-B). To explore interactions between insensitive niches and the Tumor Microenvironment (TME), Squidpy analysis revealed a positive spatial association with Niche 10, predominantly composed of immune cells like Tumor-associated Macrophages (TAMs) and T cells (Supplementary Figure S7C). Immune suppressors such as CCL18 showed elevated expression in non-pCR patients, indicating complex TME interactions (Supplementary Figure S7D-E). Higher CCL18 expression was detected in Niche 10, with increased CCL18-PITPNM3 signaling between Niches 10 and 1, 4, 6 in non-pCR patients (Supplementary Figure S7F-G). Further investigation revealed FOXQ1 and CCL18 expression significantly enriched in non-pCR patients, particularly post-neoadjuvant therapy (Supplementary Figure S8A-B). CD206<sup>+</sup>/CCL18<sup>+</sup> TAMs were predominantly located near FOXQ1<sup>+</sup> tumor cells, suggesting localized immunosuppressive interactions (Supplementary Figure S8A).</p><p>In this study, oxidative phosphorylation and FOXQ1 expression were enriched in residual tumor cells post-neoadjuvant therapy. FOXQ1, an oncogenic transcription factor, promotes complex I-linked oxidative phosphorylation by upregulating NDUFS1 and NDUFV1 [<span>8</span>]. CD206<sup>+</sup>/CCL18<sup>+</sup> TAM density differed significantly between pCR and non-pCR patients, and these TAMs were spatially near FOXQ1<sup>+</sup> tumor cells. CCL18, a key chemokine in tumor biology, induces regulatory T cell recruitment and a pro-tumor M2-like macrophage phenotype [<span>9</span>]. It also promotes cancer progression via metastasis and EMT through its receptor PITPNM3 [<span>10</span>]. The interaction between FOXQ1<sup>+</sup> tumor cells and CD206<sup>+</sup>/CCL18<sup>+</sup> TAMs needs further study.</p><p>In conclusion, the combination of anlotinib with TP neoadjuvant therapy demonstrates high clinical efficacy and a favorable safety profile in patients with resectable HNSCC. And further high-quality, multi-center, double-blind phase III RCTs with longer follow-up are needed to validate anlotinib's potential in a larger HNSCC population.</p><p><i>Conceptualization</i>: Shuojin Huang, Qianting He, Dongxiao Tang, Wanhang Zhou, Congyuan Cao, Anxun Wang, and Demeng Chen. <i>Methodology</i>: Shuojin Huang, Qianting He, Dongxiao Tang, Wanhang Zhou, and Congyuan Cao. <i>Data analysis and curation</i>: Shuojin Huang, Wanhang Zhou, Rongsong Ling, Jie Chen, and Bokai Yun. <i>Investigation and validation</i>: Shuojin Huang, Qianting He, Dongxiao Tang, Wanhang Zhou, Congyuan Cao, Xin Zheng, and Yanchen Li. <i>Resources</i>: Jie Chen, Anxun Wang, and Demeng Chen. <i>Writing-original draft</i>: Shuojin Huang, Wanhang Zhou, Anxun Wang, and Demeng Chen. <i>Writing-review &amp; editing</i>: Anxun Wang and Demeng Chen. <i>Supervision and funding acquisition</i>: Anxun Wang and Demeng Chen.</p><p>The authors declare no competing interests.</p><p>This work was supported by funding from the National Natural Science Foundation of China (No. 82173041, 82372868, 82173362, 81872409, 82304069, 82403184, and 823B2079), Guangzhou Municipal Science and Technology Bureau (No. 2024B03J1384), China Postdoctoral Science Foundation (No. 2023M734003), Natural Science Foundation of Guangdong Province (No. 2024A1515012316), and Basic and Applied Basic Research Foundation of Guangdong Province (No. 2023A1515110475).</p><p>The ethical, medical, and scientific aspects of the research were reviewed and approved by the Ethics Committee of the First Affiliated Hospital, Sun Yat-Sen University before initiation (Ethical approval number: [2022]474), and the trial was registered at the Chinese Clinical Trial Registry (ChiCTR2300078009).</p>","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":"45 5","pages":"632-636"},"PeriodicalIF":24.9000,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.70006","citationCount":"0","resultStr":"{\"title\":\"Neoadjuvant chemotherapy plus anlotinib in the treatment of resectable head and neck squamous cell carcinoma: A pilot phase II trial\",\"authors\":\"Qianting He,&nbsp;Shuojin Huang,&nbsp;Dongxiao Tang,&nbsp;Congyuan Cao,&nbsp;Wanhang Zhou,&nbsp;Rongsong Ling,&nbsp;Jie Chen,&nbsp;Bokai Yun,&nbsp;Xin Zheng,&nbsp;Yanchen Li,&nbsp;Anxun Wang,&nbsp;Demeng Chen\",\"doi\":\"10.1002/cac2.70006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Head and neck squamous cell carcinoma (HNSCC) continues to be a major global health challenge, with limited survival improvements for patients with locally advanced (LA) or recurrent (R) disease [<span>1</span>]. Anlotinib, a novel orally administered small-molecule tyrosine kinase inhibitor (TKI) developed in China, targets a wide range of receptor tyrosine kinases (RTKs) [<span>2</span>]. Our previous studies have also manifested that anlotinib remarkably inhibited the proliferation of HNSCC cells both in vitro and in vivo, and presented promising clinical antitumor efficacy and tolerable safety profile in patients with oral squamous cell carcinoma (OSCC) [<span>3, 4</span>]. This prospective trial was designed to evaluate the clinical efficacy and safety of anlotinib combined with paclitaxel and cisplatin (TP) neoadjuvant therapy in patients with resectable HNSCC. Additionally, the mechanisms underlying the effects of anlotinib and neoadjuvant chemotherapy on HNSCC were investigated through spatial transcriptomics (STs) and multiplex immunohistochemistry (mIHC).</p><p>Between October 2022 and May 2023, 20 resectable HNSCC patients were enrolled (median age, 55; range, 27-73). Baseline demographics and disease characteristics are detailed in Supplementary Tables S1-S2. All patients received 3 cycles of neoadjuvant therapy, followed by surgery in 17 and maintenance therapy in 16. No patients were lost to follow-up (study flowchart in Figure 1A). After neoadjuvant therapy, 95.0% (19/20) achieved partial response (PR), and 5.0% (1/20) achieved complete response (CR), with an Objective response rate (ORR) of 100% (95% confidence interval [CI], 83.2-100). Figure 1B shows the waterfall plot of tumor size changes. Surgical resection was performed in 17 patients (LA, 12; R, 5) with a 100% R0 resection rate, one patient declined surgery due to financial constraints and the other two did not want to perform surgery as their tumors had almost regressed. Postoperative pathological efficacy (Supplementary Table S3) showed pathological complete response (pCR) and major pathological response (MPR) in 7 patients each (41.2%; 95% CI, 18.4-67.1). Among 11 with positive cervical lymph nodes, 6 achieved pCR (54.5%; 95% CI, 23.4-83.3). Imaging and pathological data of patient #14 with CR are shown in Figure 1C-D.</p><p>All patients were followed for at least one year. Treatment responses and durations are shown in Figure 1E. By May 15, 2024, 17 out of 20 patients were alive. Of the 3 deaths, 1 patient with LA declined further therapy for financial constraints after neoadjuvant treatment and died a year later, another patient with LA refused maintenance therapy after surgery and died within a year, while one patient with LA died in a traffic accident four months post-radiotherapy. Among the all 20 patients, 5 (4 with LA and 1 with R) experienced local recurrence within 1 year. Of the 17 patients with R0 resection, 4 (3 with LA and 1 with R) had a local recurrence within 1 year.</p><p>Treatment Emergent Adverse Events (TEAEs) are summarized in Supplementary Tables S4-S5. All patients experienced at least one TEAE post-neoadjuvant therapy, primarily grades 1-2. Common TEAEs included alopecia (100%), hypertension (90%), anemia (85%), and hand-foot syndrome (45%). Grade 3 TEAEs occurred in 50% of patients. No TRAEs caused drug discontinuation, dose reduction, death, or surgical delays.</p><p>To investigate the effects of neoadjuvant therapy on HNSCC, STs were conducted using Formalin Fixed Paraffin Embedded (FFPE) samples from 4 pCR and 3 non-pCR patients (Figure 1F, Supplementary Table S6). All 48,666 capture spots passed quality control, yielding a mean of 15,016 reads per spot (52.2 million per capture) and 4,498 mapped genes per sample.</p><p>Unsupervised clustering using the Louvain algorithm identified 10 niches across 14 samples (Supplementary Figure S1A), present in varying proportions (Supplementary Figure S1B). Each spot, containing 1-10 cells, was analyzed via multimodal intersection analysis (MIA) [<span>5</span>] with Single-cell RNA sequencing (scRNA-seq) datasets (GSE234933 and GSE181919). MIA predicted high malignant cell incidence in Niches 1, 4, and 6; Cancer Associated Fibroblasts (CAFs) in Niche 2; B cells and CAFs in Niche 3; endothelial cells and CAFs in Niches 5 and 7; immune cells in Niches 8 and 10; and ambiguous markers in Niche 9 (Supplementary Figure S1C). Manual annotation with cell type markers confirmed MIA results (Supplementary Figure S1D). Copy Number Variation (CNV) analysis showed recurrent chromosome 1 deletions and chromosome 3 amplifications in Niches 1, 4, and 6, aligning with prior studies [<span>6</span>]. Some Niche 1 spots exhibited low CNV, suggesting non-malignant squamous epithelial cells (Supplementary Figure S1E-F). Mapping niches onto FFPE sections revealed tumor regions comprised Niches 1, 4, and 6, with distinct spatial distributions: in addition to posttreatment samples of pCR patients, Niche 6 is primarily located at the tumor periphery, Niche 1 at the intermediate epithelial region, and Niche 4 at the leading edge. (Supplementary Figure S2). Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) analysis inferred tumor, stromal, and immune substructures, closely matching histological annotations (Supplementary Figure S3). Non-negative matrix factorization (NMF) [<span>7</span>] identified 11 transcriptional metaprograms, including a recurrent part Epithelial-Mesenchymal Transition (pEMT) module (COL17A1, LAMA3, and LAMC2), stress response genes (S100A9, S100A8, and KRT6A), and hypoxia-response genes (ENO1, DDIT4, and VEGFA; Supplementary Figure S4A-B. Other programs corresponded to CAF (ECM-CAFs: COL1A1, COL1A2, and COL3A1; myo-CAFs: DES, ACTN2, and MYH2) and immune lineages. NMF results aligned with niche classifications (Supplementary Figure S4C-D).</p><p>To further examine treatment effects on HNSCC, we analyzed niche compositions before and after treatment. Posttreatment samples showed significant decreases in Niche 4 and Niche 6 (Niche 4: 23.9% to 2.8%; Niche 6: 13.4% to 5.2%), reflecting a robust anti-tumor effect (Supplementary Figure S5A). Conversely, Niche 3, 5, 7, and 8 increased posttreatments (Niche 3: 6.9% to 16.9%; Niche 5: 7.6% to 13.4%; Niche 7: 4.7% to 7.3%; Niche 8: 2.1% to 8.3%). Gene Set Variation Analysis (GSVA) analysis revealed upregulated mRNAs in posttreatment samples enriched in pathways related to B cell receptor signaling, complement action, and adaptive immune response, while downregulated mRNAs were linked to epidermis development and cell cycle regulation (Supplementary Figure S5B). Niche 3, primarily composed of B cells and CAFs (Supplementary Figure S1C), was located near tumor niches (Supplementary Figure S2), suggesting interactions with tumor cells. Transcriptomic analysis showed that pretreatment Niche 3 was associated with extracellular matrix (ECM) markers (e.g., COL7A1 and DSP), while posttreatment samples displayed upregulation of immune regulatory genes and B cell activation markers (e.g., IGHG3, IGLC1, SFRP2, and SFPR4; Supplementary Figure S5C). Gene Set Enrichment Analysis (GSEA) confirmed enrichment of immune response and B cell-mediated immunity gene sets in posttreatment Niche 3 (Supplementary Figure S5D). CellChat analysis revealed increased communication strength between Niche 3 and tumor niches (Niche 1, 4, and 6) after treatment (Supplementary Figure S5E-F). Ligand-receptor pairs (C3-ITGAX + ITGB2, CCL5-ACKR1, and SEMA3C-PLXND1) were significantly upregulated posttreatment, suggesting their role in anti-tumor immunity (Supplementary Figure S5G). Flow pattern showed dominant SEMA3, CCL, ANGPTL, and COMPLEMENT signaling pathways posttreatment, whereas VEGFA, VISFATIN, NRG, and ncWNT were predominant pretreatment (Supplementary Figure S5H).</p><p>To delineate key molecular characteristics of non-pCR samples, we manually selected spots from residual tumors (Supplementary Figure S6A) and identified an insensitive signature score via Differential Expression Gene (DEG) analysis between residual tumor cells and other niches (Supplementary Figure S6B-C). GSEA revealed upregulated genes enriched in pathways, such as oxidative phosphorylation, MYC targets, DNA repair, and interferon alpha response (Supplementary Figure S6D-E). Using high-dimensional Weighted Gene Co-expression Network Analysis (hdWGCNA), we identified seven gene modules, with Module RN4 showing the highest positive correlation to the insensitive score (Supplementary Figure S6F-H). Python-based Single-Cell Regulatory Network Inference and Clustering (PySCENIC) analysis revealed differentially activated transcription factors (TFs), including HES1, FOXQ1, and FOXA1, in the insensitive niche (Supplementary Figure S6I).</p><p>Notably, FOXQ1 was consistently identified across datasets and was significantly enriched in naïve non-pCR samples compared to naïve pCR samples, suggesting its key role in tumor cell insensitivity (Supplementary Figure S7A-B). To explore interactions between insensitive niches and the Tumor Microenvironment (TME), Squidpy analysis revealed a positive spatial association with Niche 10, predominantly composed of immune cells like Tumor-associated Macrophages (TAMs) and T cells (Supplementary Figure S7C). Immune suppressors such as CCL18 showed elevated expression in non-pCR patients, indicating complex TME interactions (Supplementary Figure S7D-E). Higher CCL18 expression was detected in Niche 10, with increased CCL18-PITPNM3 signaling between Niches 10 and 1, 4, 6 in non-pCR patients (Supplementary Figure S7F-G). Further investigation revealed FOXQ1 and CCL18 expression significantly enriched in non-pCR patients, particularly post-neoadjuvant therapy (Supplementary Figure S8A-B). CD206<sup>+</sup>/CCL18<sup>+</sup> TAMs were predominantly located near FOXQ1<sup>+</sup> tumor cells, suggesting localized immunosuppressive interactions (Supplementary Figure S8A).</p><p>In this study, oxidative phosphorylation and FOXQ1 expression were enriched in residual tumor cells post-neoadjuvant therapy. FOXQ1, an oncogenic transcription factor, promotes complex I-linked oxidative phosphorylation by upregulating NDUFS1 and NDUFV1 [<span>8</span>]. CD206<sup>+</sup>/CCL18<sup>+</sup> TAM density differed significantly between pCR and non-pCR patients, and these TAMs were spatially near FOXQ1<sup>+</sup> tumor cells. CCL18, a key chemokine in tumor biology, induces regulatory T cell recruitment and a pro-tumor M2-like macrophage phenotype [<span>9</span>]. It also promotes cancer progression via metastasis and EMT through its receptor PITPNM3 [<span>10</span>]. The interaction between FOXQ1<sup>+</sup> tumor cells and CD206<sup>+</sup>/CCL18<sup>+</sup> TAMs needs further study.</p><p>In conclusion, the combination of anlotinib with TP neoadjuvant therapy demonstrates high clinical efficacy and a favorable safety profile in patients with resectable HNSCC. And further high-quality, multi-center, double-blind phase III RCTs with longer follow-up are needed to validate anlotinib's potential in a larger HNSCC population.</p><p><i>Conceptualization</i>: Shuojin Huang, Qianting He, Dongxiao Tang, Wanhang Zhou, Congyuan Cao, Anxun Wang, and Demeng Chen. <i>Methodology</i>: Shuojin Huang, Qianting He, Dongxiao Tang, Wanhang Zhou, and Congyuan Cao. <i>Data analysis and curation</i>: Shuojin Huang, Wanhang Zhou, Rongsong Ling, Jie Chen, and Bokai Yun. <i>Investigation and validation</i>: Shuojin Huang, Qianting He, Dongxiao Tang, Wanhang Zhou, Congyuan Cao, Xin Zheng, and Yanchen Li. <i>Resources</i>: Jie Chen, Anxun Wang, and Demeng Chen. <i>Writing-original draft</i>: Shuojin Huang, Wanhang Zhou, Anxun Wang, and Demeng Chen. <i>Writing-review &amp; editing</i>: Anxun Wang and Demeng Chen. <i>Supervision and funding acquisition</i>: Anxun Wang and Demeng Chen.</p><p>The authors declare no competing interests.</p><p>This work was supported by funding from the National Natural Science Foundation of China (No. 82173041, 82372868, 82173362, 81872409, 82304069, 82403184, and 823B2079), Guangzhou Municipal Science and Technology Bureau (No. 2024B03J1384), China Postdoctoral Science Foundation (No. 2023M734003), Natural Science Foundation of Guangdong Province (No. 2024A1515012316), and Basic and Applied Basic Research Foundation of Guangdong Province (No. 2023A1515110475).</p><p>The ethical, medical, and scientific aspects of the research were reviewed and approved by the Ethics Committee of the First Affiliated Hospital, Sun Yat-Sen University before initiation (Ethical approval number: [2022]474), and the trial was registered at the Chinese Clinical Trial Registry (ChiCTR2300078009).</p>\",\"PeriodicalId\":9495,\"journal\":{\"name\":\"Cancer Communications\",\"volume\":\"45 5\",\"pages\":\"632-636\"},\"PeriodicalIF\":24.9000,\"publicationDate\":\"2025-02-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.70006\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Communications\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cac2.70006\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Communications","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cac2.70006","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
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摘要

在FFPE切片上绘制壁龛图,发现肿瘤区域包括壁龛1、4和6,且空间分布明显:除了pCR患者治疗后的样本外,壁龛6主要位于肿瘤周边,壁龛1位于中间上皮区,壁龛4位于前沿。(补充图S2)。利用表达数据(ESTIMATE)分析推断肿瘤、间质和免疫亚结构,与组织学注释密切匹配(补充图S3)。非阴性基质因子分解(NMF)鉴定了11个转录元程序,包括复发部分上皮-间质转化(pEMT)模块(COL17A1、LAMA3和LAMC2)、应激反应基因(S100A9、S100A8和KRT6A)和缺氧反应基因(ENO1、DDIT4和VEGFA;补充图S4A-B其他与CAF相对应的程序(ecm - cas: COL1A1、COL1A2和COL3A1;myo-CAFs: DES, ACTN2和MYH2)和免疫谱系。NMF结果与生态位分类一致(补充图S4C-D)。为了进一步研究治疗效果,我们分析了治疗前后生态位组成。处理后的生态位4和生态位6显著降低(生态位4:23.9% ~ 2.8%;小生境6:13.4%至5.2%),反映出强大的抗肿瘤作用(Supplementary Figure S5A)。相反,生态位3、5、7和8增加了后处理(生态位3:6.9% ~ 16.9%;利基5:7.6% - 13.4%;生态位7:4.7% - 7.3%;利基8:2.1% - 8.3%)。基因集变异分析(GSVA)分析显示,在处理后的样品中,mrna的上调富集于与B细胞受体信号传导、补体作用和适应性免疫反应相关的途径,而mrna的下调与表皮发育和细胞周期调节有关(补充图S5B)。小生境3主要由B细胞和CAFs组成(Supplementary图S1C),位于肿瘤小生境附近(Supplementary图S2),提示与肿瘤细胞相互作用。转录组学分析显示,预处理后的小生境3与细胞外基质(ECM)标记物(如COL7A1和DSP)相关,而处理后的样品显示免疫调节基因和B细胞激活标记物(如IGHG3、IGLC1、SFRP2和SFPR4)上调;补充图S5C)。基因集富集分析(GSEA)证实免疫应答和B细胞介导的免疫基因集在治疗后的生态位3中富集(补充图S5D)。CellChat分析显示,治疗后3号生态位与肿瘤生态位(1、4和6号生态位)之间的通信强度增加(补充图S5E-F)。配体受体对(C3-ITGAX + ITGB2、CCL5-ACKR1和SEMA3C-PLXND1)在治疗后显著上调,提示其在抗肿瘤免疫中的作用(Supplementary Figure S5G)。血流模式显示处理后的信号通路以SEMA3、CCL、ANGPTL和COMPLEMENT为主,而预处理后的信号通路以VEGFA、VISFATIN、NRG和ncWNT为主(Supplementary Figure S5H)。为了描述非pcr样本的关键分子特征,我们手动从残留肿瘤中选择点(补充图S6A),并通过残留肿瘤细胞与其他壁位之间的差异表达基因(DEG)分析确定不敏感的特征评分(补充图S6B-C)。GSEA揭示了氧化磷酸化、MYC靶点、DNA修复和干扰素α反应等通路中富集的上调基因(补充图S6D-E)。使用高维加权基因共表达网络分析(hdWGCNA),我们确定了7个基因模块,其中模块RN4与不敏感评分的正相关性最高(补充图S6F-H)。基于python的单细胞调节网络推断和聚类(PySCENIC)分析显示,在不敏感的生态位中存在差异激活的转录因子(TFs),包括HES1、FOXQ1和FOXA1 (Supplementary Figure S6I)。值得注意的是,FOXQ1在各个数据集中都得到了一致的鉴定,并且与naïve pCR样品相比,FOXQ1在naïve非pCR样品中显著富集,这表明它在肿瘤细胞不敏感中起着关键作用(Supplementary Figure S7A-B)。为了探索不敏感生态位与肿瘤微环境(TME)之间的相互作用,Squidpy分析显示与生态位10呈正相关,主要由肿瘤相关巨噬细胞(tam)和T细胞等免疫细胞组成(补充图S7C)。免疫抑制因子如CCL18在非pcr患者中表达升高,表明复杂的TME相互作用(补充图S7D-E)。CCL18在生态位10中表达较高,在非pcr患者中,CCL18- pitpnm3信号在生态位10和1、4、6之间增加(补充图S7F-G)。 进一步的研究显示,FOXQ1和CCL18的表达在非pcr患者中显著富集,特别是在新辅助治疗后(补充图S8A-B)。CD206+/CCL18+ tam主要位于FOXQ1+肿瘤细胞附近,提示局部免疫抑制相互作用(补充图S8A)。在本研究中,氧化磷酸化和FOXQ1的表达在新辅助治疗后的残余肿瘤细胞中富集。FOXQ1是一种致癌转录因子,通过上调NDUFS1和NDUFV1[8]来促进复合体i相关的氧化磷酸化。CD206+/CCL18+ TAM密度在pCR和非pCR患者之间差异显著,且这些TAM在空间上靠近FOXQ1+肿瘤细胞。CCL18是肿瘤生物学中的关键趋化因子,可诱导调节性T细胞募集和促肿瘤m2样巨噬细胞表型[9]。它还通过其受体PITPNM3[10]通过转移和EMT促进癌症进展。FOXQ1+肿瘤细胞与CD206+/CCL18+ tam之间的相互作用有待进一步研究。综上所述,anlotinib联合TP新辅助治疗在可切除的HNSCC患者中具有较高的临床疗效和良好的安全性。需要进一步的高质量、多中心、双盲、更长随访期的III期随机对照试验来验证anlotinib在更大的HNSCC人群中的潜力。概念:黄烁金、何倩婷、唐东晓、周万航、曹从远、王安勋、陈德萌。方法学:黄朔金、何倩婷、唐东晓、周万航、曹从元。数据分析与策展:黄朔金、周万航、凌荣松、陈杰、云博开。调查验证:黄朔金,何倩婷,唐东晓,周万航,曹从元,郑鑫,李彦辰。资源:陈杰,王安勋,陈德萌。原稿:黄朔金、周万航、王安勋、陈德萌。Writing-review,编辑:王安勋、陈德萌。监管与资金收购:王安勋、陈德萌。作者声明没有利益冲突。国家自然科学基金(No. 82173041, 82372868, 82173362, 81872409, 82304069, 82403184, 823B2079),广州市科技局(No. 2024B03J1384),中国博士后科学基金(No. 2023M734003),广东省自然科学基金(No. 2024A1515012316),广东省基础与应用基础研究基金(No. 2023A1515110475)资助。本研究的伦理、医学和科学方面在启动前由中山大学第一附属医院伦理委员会审查和批准(伦理批准号:[2022]474),并在中国临床试验注册中心注册(ChiCTR2300078009)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Neoadjuvant chemotherapy plus anlotinib in the treatment of resectable head and neck squamous cell carcinoma: A pilot phase II trial

Neoadjuvant chemotherapy plus anlotinib in the treatment of resectable head and neck squamous cell carcinoma: A pilot phase II trial

Head and neck squamous cell carcinoma (HNSCC) continues to be a major global health challenge, with limited survival improvements for patients with locally advanced (LA) or recurrent (R) disease [1]. Anlotinib, a novel orally administered small-molecule tyrosine kinase inhibitor (TKI) developed in China, targets a wide range of receptor tyrosine kinases (RTKs) [2]. Our previous studies have also manifested that anlotinib remarkably inhibited the proliferation of HNSCC cells both in vitro and in vivo, and presented promising clinical antitumor efficacy and tolerable safety profile in patients with oral squamous cell carcinoma (OSCC) [3, 4]. This prospective trial was designed to evaluate the clinical efficacy and safety of anlotinib combined with paclitaxel and cisplatin (TP) neoadjuvant therapy in patients with resectable HNSCC. Additionally, the mechanisms underlying the effects of anlotinib and neoadjuvant chemotherapy on HNSCC were investigated through spatial transcriptomics (STs) and multiplex immunohistochemistry (mIHC).

Between October 2022 and May 2023, 20 resectable HNSCC patients were enrolled (median age, 55; range, 27-73). Baseline demographics and disease characteristics are detailed in Supplementary Tables S1-S2. All patients received 3 cycles of neoadjuvant therapy, followed by surgery in 17 and maintenance therapy in 16. No patients were lost to follow-up (study flowchart in Figure 1A). After neoadjuvant therapy, 95.0% (19/20) achieved partial response (PR), and 5.0% (1/20) achieved complete response (CR), with an Objective response rate (ORR) of 100% (95% confidence interval [CI], 83.2-100). Figure 1B shows the waterfall plot of tumor size changes. Surgical resection was performed in 17 patients (LA, 12; R, 5) with a 100% R0 resection rate, one patient declined surgery due to financial constraints and the other two did not want to perform surgery as their tumors had almost regressed. Postoperative pathological efficacy (Supplementary Table S3) showed pathological complete response (pCR) and major pathological response (MPR) in 7 patients each (41.2%; 95% CI, 18.4-67.1). Among 11 with positive cervical lymph nodes, 6 achieved pCR (54.5%; 95% CI, 23.4-83.3). Imaging and pathological data of patient #14 with CR are shown in Figure 1C-D.

All patients were followed for at least one year. Treatment responses and durations are shown in Figure 1E. By May 15, 2024, 17 out of 20 patients were alive. Of the 3 deaths, 1 patient with LA declined further therapy for financial constraints after neoadjuvant treatment and died a year later, another patient with LA refused maintenance therapy after surgery and died within a year, while one patient with LA died in a traffic accident four months post-radiotherapy. Among the all 20 patients, 5 (4 with LA and 1 with R) experienced local recurrence within 1 year. Of the 17 patients with R0 resection, 4 (3 with LA and 1 with R) had a local recurrence within 1 year.

Treatment Emergent Adverse Events (TEAEs) are summarized in Supplementary Tables S4-S5. All patients experienced at least one TEAE post-neoadjuvant therapy, primarily grades 1-2. Common TEAEs included alopecia (100%), hypertension (90%), anemia (85%), and hand-foot syndrome (45%). Grade 3 TEAEs occurred in 50% of patients. No TRAEs caused drug discontinuation, dose reduction, death, or surgical delays.

To investigate the effects of neoadjuvant therapy on HNSCC, STs were conducted using Formalin Fixed Paraffin Embedded (FFPE) samples from 4 pCR and 3 non-pCR patients (Figure 1F, Supplementary Table S6). All 48,666 capture spots passed quality control, yielding a mean of 15,016 reads per spot (52.2 million per capture) and 4,498 mapped genes per sample.

Unsupervised clustering using the Louvain algorithm identified 10 niches across 14 samples (Supplementary Figure S1A), present in varying proportions (Supplementary Figure S1B). Each spot, containing 1-10 cells, was analyzed via multimodal intersection analysis (MIA) [5] with Single-cell RNA sequencing (scRNA-seq) datasets (GSE234933 and GSE181919). MIA predicted high malignant cell incidence in Niches 1, 4, and 6; Cancer Associated Fibroblasts (CAFs) in Niche 2; B cells and CAFs in Niche 3; endothelial cells and CAFs in Niches 5 and 7; immune cells in Niches 8 and 10; and ambiguous markers in Niche 9 (Supplementary Figure S1C). Manual annotation with cell type markers confirmed MIA results (Supplementary Figure S1D). Copy Number Variation (CNV) analysis showed recurrent chromosome 1 deletions and chromosome 3 amplifications in Niches 1, 4, and 6, aligning with prior studies [6]. Some Niche 1 spots exhibited low CNV, suggesting non-malignant squamous epithelial cells (Supplementary Figure S1E-F). Mapping niches onto FFPE sections revealed tumor regions comprised Niches 1, 4, and 6, with distinct spatial distributions: in addition to posttreatment samples of pCR patients, Niche 6 is primarily located at the tumor periphery, Niche 1 at the intermediate epithelial region, and Niche 4 at the leading edge. (Supplementary Figure S2). Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) analysis inferred tumor, stromal, and immune substructures, closely matching histological annotations (Supplementary Figure S3). Non-negative matrix factorization (NMF) [7] identified 11 transcriptional metaprograms, including a recurrent part Epithelial-Mesenchymal Transition (pEMT) module (COL17A1, LAMA3, and LAMC2), stress response genes (S100A9, S100A8, and KRT6A), and hypoxia-response genes (ENO1, DDIT4, and VEGFA; Supplementary Figure S4A-B. Other programs corresponded to CAF (ECM-CAFs: COL1A1, COL1A2, and COL3A1; myo-CAFs: DES, ACTN2, and MYH2) and immune lineages. NMF results aligned with niche classifications (Supplementary Figure S4C-D).

To further examine treatment effects on HNSCC, we analyzed niche compositions before and after treatment. Posttreatment samples showed significant decreases in Niche 4 and Niche 6 (Niche 4: 23.9% to 2.8%; Niche 6: 13.4% to 5.2%), reflecting a robust anti-tumor effect (Supplementary Figure S5A). Conversely, Niche 3, 5, 7, and 8 increased posttreatments (Niche 3: 6.9% to 16.9%; Niche 5: 7.6% to 13.4%; Niche 7: 4.7% to 7.3%; Niche 8: 2.1% to 8.3%). Gene Set Variation Analysis (GSVA) analysis revealed upregulated mRNAs in posttreatment samples enriched in pathways related to B cell receptor signaling, complement action, and adaptive immune response, while downregulated mRNAs were linked to epidermis development and cell cycle regulation (Supplementary Figure S5B). Niche 3, primarily composed of B cells and CAFs (Supplementary Figure S1C), was located near tumor niches (Supplementary Figure S2), suggesting interactions with tumor cells. Transcriptomic analysis showed that pretreatment Niche 3 was associated with extracellular matrix (ECM) markers (e.g., COL7A1 and DSP), while posttreatment samples displayed upregulation of immune regulatory genes and B cell activation markers (e.g., IGHG3, IGLC1, SFRP2, and SFPR4; Supplementary Figure S5C). Gene Set Enrichment Analysis (GSEA) confirmed enrichment of immune response and B cell-mediated immunity gene sets in posttreatment Niche 3 (Supplementary Figure S5D). CellChat analysis revealed increased communication strength between Niche 3 and tumor niches (Niche 1, 4, and 6) after treatment (Supplementary Figure S5E-F). Ligand-receptor pairs (C3-ITGAX + ITGB2, CCL5-ACKR1, and SEMA3C-PLXND1) were significantly upregulated posttreatment, suggesting their role in anti-tumor immunity (Supplementary Figure S5G). Flow pattern showed dominant SEMA3, CCL, ANGPTL, and COMPLEMENT signaling pathways posttreatment, whereas VEGFA, VISFATIN, NRG, and ncWNT were predominant pretreatment (Supplementary Figure S5H).

To delineate key molecular characteristics of non-pCR samples, we manually selected spots from residual tumors (Supplementary Figure S6A) and identified an insensitive signature score via Differential Expression Gene (DEG) analysis between residual tumor cells and other niches (Supplementary Figure S6B-C). GSEA revealed upregulated genes enriched in pathways, such as oxidative phosphorylation, MYC targets, DNA repair, and interferon alpha response (Supplementary Figure S6D-E). Using high-dimensional Weighted Gene Co-expression Network Analysis (hdWGCNA), we identified seven gene modules, with Module RN4 showing the highest positive correlation to the insensitive score (Supplementary Figure S6F-H). Python-based Single-Cell Regulatory Network Inference and Clustering (PySCENIC) analysis revealed differentially activated transcription factors (TFs), including HES1, FOXQ1, and FOXA1, in the insensitive niche (Supplementary Figure S6I).

Notably, FOXQ1 was consistently identified across datasets and was significantly enriched in naïve non-pCR samples compared to naïve pCR samples, suggesting its key role in tumor cell insensitivity (Supplementary Figure S7A-B). To explore interactions between insensitive niches and the Tumor Microenvironment (TME), Squidpy analysis revealed a positive spatial association with Niche 10, predominantly composed of immune cells like Tumor-associated Macrophages (TAMs) and T cells (Supplementary Figure S7C). Immune suppressors such as CCL18 showed elevated expression in non-pCR patients, indicating complex TME interactions (Supplementary Figure S7D-E). Higher CCL18 expression was detected in Niche 10, with increased CCL18-PITPNM3 signaling between Niches 10 and 1, 4, 6 in non-pCR patients (Supplementary Figure S7F-G). Further investigation revealed FOXQ1 and CCL18 expression significantly enriched in non-pCR patients, particularly post-neoadjuvant therapy (Supplementary Figure S8A-B). CD206+/CCL18+ TAMs were predominantly located near FOXQ1+ tumor cells, suggesting localized immunosuppressive interactions (Supplementary Figure S8A).

In this study, oxidative phosphorylation and FOXQ1 expression were enriched in residual tumor cells post-neoadjuvant therapy. FOXQ1, an oncogenic transcription factor, promotes complex I-linked oxidative phosphorylation by upregulating NDUFS1 and NDUFV1 [8]. CD206+/CCL18+ TAM density differed significantly between pCR and non-pCR patients, and these TAMs were spatially near FOXQ1+ tumor cells. CCL18, a key chemokine in tumor biology, induces regulatory T cell recruitment and a pro-tumor M2-like macrophage phenotype [9]. It also promotes cancer progression via metastasis and EMT through its receptor PITPNM3 [10]. The interaction between FOXQ1+ tumor cells and CD206+/CCL18+ TAMs needs further study.

In conclusion, the combination of anlotinib with TP neoadjuvant therapy demonstrates high clinical efficacy and a favorable safety profile in patients with resectable HNSCC. And further high-quality, multi-center, double-blind phase III RCTs with longer follow-up are needed to validate anlotinib's potential in a larger HNSCC population.

Conceptualization: Shuojin Huang, Qianting He, Dongxiao Tang, Wanhang Zhou, Congyuan Cao, Anxun Wang, and Demeng Chen. Methodology: Shuojin Huang, Qianting He, Dongxiao Tang, Wanhang Zhou, and Congyuan Cao. Data analysis and curation: Shuojin Huang, Wanhang Zhou, Rongsong Ling, Jie Chen, and Bokai Yun. Investigation and validation: Shuojin Huang, Qianting He, Dongxiao Tang, Wanhang Zhou, Congyuan Cao, Xin Zheng, and Yanchen Li. Resources: Jie Chen, Anxun Wang, and Demeng Chen. Writing-original draft: Shuojin Huang, Wanhang Zhou, Anxun Wang, and Demeng Chen. Writing-review & editing: Anxun Wang and Demeng Chen. Supervision and funding acquisition: Anxun Wang and Demeng Chen.

The authors declare no competing interests.

This work was supported by funding from the National Natural Science Foundation of China (No. 82173041, 82372868, 82173362, 81872409, 82304069, 82403184, and 823B2079), Guangzhou Municipal Science and Technology Bureau (No. 2024B03J1384), China Postdoctoral Science Foundation (No. 2023M734003), Natural Science Foundation of Guangdong Province (No. 2024A1515012316), and Basic and Applied Basic Research Foundation of Guangdong Province (No. 2023A1515110475).

The ethical, medical, and scientific aspects of the research were reviewed and approved by the Ethics Committee of the First Affiliated Hospital, Sun Yat-Sen University before initiation (Ethical approval number: [2022]474), and the trial was registered at the Chinese Clinical Trial Registry (ChiCTR2300078009).

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来源期刊
Cancer Communications
Cancer Communications Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
25.50
自引率
4.30%
发文量
153
审稿时长
4 weeks
期刊介绍: Cancer Communications is an open access, peer-reviewed online journal that encompasses basic, clinical, and translational cancer research. The journal welcomes submissions concerning clinical trials, epidemiology, molecular and cellular biology, and genetics.
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