The Efficacy and Response Predictors of Platinum-Based Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer

Targeting tumor-associated macrophage-derived CD74 improves efficacy of neoadjuvant chemotherapy in combination with PD-1 blockade for cervical cancer

BACKGROUND

Cervical cancer has the second-highest mortality rate among malignant tumors of the female reproductive system. Immune checkpoint inhibitors such as programmed cell death protein 1 (PD-1) blockade are promising therapeutic agents, but their efficacy when combined with neoadjuvant chemotherapy (NACT) has not been fully tested, and how they alter the tumor microenvironment has not been comprehensively elucidated.

METHODS

In this study, we conducted single-cell RNA sequencing using 46,950 cells from nine human cervical cancer tissues representing sequential different stages of NACT and PD-1 blockade combination therapy. We delineated the trajectory of cervical epithelial cells and identified the crucial factors involved in combination therapy. Cell-cell communication analysis was performed between tumor and immune cells. In addition, THP-1-derived and primary monocyte-derived macrophages were cocultured with cervical cancer cells and phagocytosis was detected by flow cytometry. The antitumor activity of blocking CD74 was validated in vivo using a CD74 humanized subcutaneous tumor model.

RESULTS

Pathway enrichment analysis indicated that NACT activated cytokine and complement-related immune responses. Cell-cell communication analysis revealed that after NACT therapy, interaction strength between T cells and cancer cells decreased, but intensified between macrophages and cancer cells. We verified that macrophages were necessary for the PD-1 blockade to exert antitumor effects in vitro. Additionally, CD74-positive macrophages frequently interacted with the most immunoreactive epithelial subgroup 3 (Epi3) cancer subgroup during combination NACT. We found that CD74 upregulation limited phagocytosis and stimulated M2 polarization, whereas CD74 blockade enhanced macrophage phagocytosis, decreasing cervical cancer cell viability in vitro and in vivo.

CONCLUSIONS

Our study reveals the dynamic cell-cell interaction network in the cervical cancer microenvironment influenced by combining NACT and PD-1 blockade. Furthermore, blocking tumor-associated macrophage-derived CD74 could augment neoadjuvant therapeutic efficacy.

Radiomics analysis for prediction of lymph node metastasis after neoadjuvant chemotherapy based on pretreatment MRI in patients with locally advanced cervical cancer

Background

This study aims to develop and validate a pretreatment MRI-based radiomics model to predict lymph node metastasis (LNM) following neoadjuvant chemotherapy (NACT) in patients with locally advanced cervical cancer (LACC).

Methods

Patients with LACC who underwent NACT from two centers between 2013 and 2022 were enrolled retrospectively. Based on the lymph node (LN) status determined in the pathology reports after radical hysterectomy, patients were categorized as LN positive or negative. The patients from center 1 were assigned as the training set while those from center 2 formed the validation set. Radiomics features were extracted from pretreatment sagittal T2-weighted imaging (Sag-T2WI), axial diffusion-weighted imaging (Ax-DWI), and the delayed phase of dynamic contrast-enhanced sagittal T1-weighted imaging (Sag-T1C) for each patient. The K-best and least absolute shrinkage and selection operator (LASSO) methods were employed to reduce dimensionality, and the radiomics features strongly associated with LNM were selected and used to construct three single-sequence models. Furthermore, clinical variables were incorporated through multivariate regression analysis and fused with the selected radiomics features to construct the clinical-radiomics combined model. The diagnostic performance of the models was assessed using receiver operating characteristic (ROC) curve analysis. The clinical utility of the models was evaluated by the area under the ROC curve (AUC) and decision curve analysis (DCA).

Results

A total of 282 patients were included, comprising 171 patients in the training set, and 111 patients in the validation set. Compared to the Sag-T2WI model (AUC, 95%CI, training set, 0.797, 0.722-0.782; validation set, 0.648, 0.521-0.776) and the Sag-T1C model (AUC, 95%CI, training set, 0.802, 0.723-0.882; validation set, 0.630, 0.505-0.756), the Ax-DWI model exhibited the highest diagnostic performance with AUCs of 0.855 (95%CI, 0.791-0.919) in training set, and 0.753 (95%CI, 0.638-0.867) in validation set, respectively. The combined model, integrating selected features from three sequences and FIGO stage, surpassed predictive ability compared to the single-sequence models, with AUC of 0.889 (95%CI, 0.833-0.945) and 0.859 (95%CI, 0.781-0.936) in the training and validation sets, respectively.

Conclusions

The pretreatment MRI-based radiomics model, integrating radiomics features from three sequences and clinical variables, exhibited superior performance in predicting LNM following NACT in patients with LACC.

PBRM1 presents a potential ctDNA marker to monitor response to neoadjuvant chemotherapy in cervical cancer

Neoadjuvant chemotherapy (NACT) is a therapeutic option for locally advanced cervical cancer (LACC) patients. This study was aimed to identify potential liquid biopsy biomarkers to monitor the NACT response. Through targeted next-generation sequencing (NGS) analysis of circulating tumor DNA (ctDNA) and tumor tissue DNA (ttDNA) taken from LACC patients undergoing platinum-based NACT, 64 genes with mutations emerge during NACT in the non-responders but none in the responders. Among them, the PBRM1, SETD2, and ROS1 mutations were frequently detected in the ctDNA and ttDNA of the non-responders, and mutant PBRM1 was associated with poorer survival of patients. In vitro, PBRM1 knockdown promoted resistance to cisplatin through boosting STAT3 signaling in cervical cancer cells, while it sensitized tumor cells to poly-ADP-ribose-polymerase inhibitor olaparib. These findings suggest that mutant PBRM1 is a potential ctDNA marker of emerging resistance to NACT and of increased sensitivity to olaparib, which warrants further clinical validation.

The prognostic value of radiological and pathological lymph node status in patients with cervical cancer who underwent neoadjuvant chemotherapy and followed hysterectomy

To investigate the prognostic value of lymph node status in patients with cervical cancer (CC) patients who underwent neoadjuvant chemotherapy (NACT) and followed hysterectomy. Patients in two referral centers were retrospectively analyzed. The baseline tumor size and radiological lymph node status (LNr) were evaluated on pre-NACT MRI. Tumor histology, differentiation and pathological lymph node status (LNp) were obtained from post-operative specimen. The log-rank test was used to compare survival between patient groups. Cox proportional hazards regression models were employed to estimate the hazard ratio (HR) of various factors with progression-free survival (PFS) and overall survival (OS). A total of 266 patients were included. Patients with 2018 FIGO IIIC showed worse PFS compared to those with FIGO IB-IIB (p < 0.001). The response rate in patients with LNp(-) was 64.1% (134/209), significantly higher than that of 45.6% (26/57) in patients with LNp( +) (p = 0.011). Multivariate Cox analysis identified the main independent predictors of PFS as LNp( +) (HR = 3.777; 95% CI 1.715-8.319), non-SCC (HR = 2.956; 95% CI 1.297-6.736), poor differentiation (HR = 2.370; 95% CI 1.130-4.970) and adjuvant radiation (HR = 3.266; 95% CI 1.183-9.019). The interaction between LNr and LNp regarding PFS were significant both for univariate and multivariate (P = 0.000171 and 1.5357e-7 respectively). In patients with LNr( +), a significant difference in PFS was observed between patients with LNp(-) and LNp( +) (p = 0.0027). CC patients with FIGO 2018 stage IIIC who underwent NACT and followed hysterectomy had worse PFS compared to those with IB-IIB. LNp( +), non-SCC, poor differentiation and adjuvant radiation were independent risk factors for PFS. The adverse prognostic value of LNp( +) was more significant in patients with LNr( +).

Improving the efficacy and safety of concurrent chemoradiotherapy by neoadjuvant chemotherapy: a randomized controlled study of locally advanced cervical cancer with a large tumor

OBJECTIVE

To compare the efficacy and safety of neoadjuvant chemotherapy combined with concurrent chemoradiotherapy (NACT+CCRT) vs. concurrent chemoradiotherapy (CCRT) in locally advanced cervical cancer (LACC) patients with large tumor masses.

METHODS

LACC patients with localized tumor diameter >4 cm, were randomly allocated in an unblinded 1:1 ratio to NACT+CCRT or CCRT groups. Patients in the NACT+CCRT group were given paclitaxel combined with cisplatin (TP) NACT every 3 weeks for 2 cycles, followed by CCRT, with the chemotherapy regimen the same as for NACT. CCRT group were given CCRT with the same as for NACT.

RESULTS

From March 1, 2019, to June 30, 2021, 146 patients were included in the final analysis. Sixty-eight (93.2%) patients in the NACT+CCRT group and 66 (90.4%) patients in the CCRT group completed the expected treatment course. The complete response (CR) rate in the NACT+CCRT group was significantly higher than in the CCRT group (87.7% vs. 67.6%, χ²=54.540, p=0.000). In the NACT+CCRT group, the 1- and 2-year overall survival (OS) rates were significantly higher than those in the CCRT group (96% vs. 89% and 89% vs. 79%, χ²=5.737, p=0.017). Additionally, the rate of recurrences and distant metastases was significantly lower in the NACT+CCRT group than in the CCRT group (4.11% vs. 7.35%, χ²=4.059, p=0.021). Most treatment-related adverse events in both groups were grade 3.

CONCLUSION

Compared to CCRT, NACT+CCRT might improve the treatment completion rate, increase CR rate and 1- and 2-year OS rates, and reduce distant metastases rate for LACC patients with large tumor masses.

Successful neoadjuvant chemotherapy plus sintilimab for locally advanced cervical cancer: case series and review of the literature

BACKGROUND

The locally advanced cervical cancer (LACC) of FIGO stage IB3-IIA2 is characterized by large local mass, poor prognosis and survival rate. Tumor response to neoadjuvant chemotherapy for LACC, utilized as a surrogate endpoint, is urgently needed to improve. Given that the antitumor immune response can be suppressed by programed death-1 axis, the treatment paradigm of neoadjuvant chemotherapy combined with immunotherapy has been explored as one of the prognostic treatments in a variety of solid carcinoma. So far, the application of sintilimab, a domestic immune checkpoint inhibitor, combined with neoadjuvant chemotherapy is still limited in LACC, especially in large lesions.

CASE DESCRIPTION

We present three postmenopausal women diagnosed with FIGO stage IB3-IIA2 cervical squamous cell carcinoma with lesions larger than 5 cm. Demographic, clinical, histopathological, laboratory and imaging data were record. At the completion of the neoadjuvant therapy with paclitaxel plus carboplatin combined with sintilimab, all patients underwent hysterectomy. After neoadjuvant treatment, a pathologic complete response in case 1 and partial responses in case 2 and case 3 were achieved, and neither patient showed any relapse during the follow-up period of 16 to 22 months.

CONCLUSIONS

This report provide evidence to support the combination of sintilimab with neoadjuvant chemotherapy in cervical cancer, which has yet to be validated in prospective studies. More clinical data are needed to verify the effectiveness of the combined regimens. This literature review also collected studies involving potential predictors of response to NACT and immunotherapy, which would be helpful in stratifying patients for future trials.

Intact glycopeptides identified by LC-MS/MS as biomarkers for response to chemotherapy of locally advanced cervical cancer

Objective

For locally advanced cervical cancer (LACC), patients who respond to chemotherapy have a potential survival advantage compared to nonresponsive patients. Thus, it is necessary to explore specific biological markers for the efficacy of chemotherapy, which is beneficial to personalized treatment.

Methods

In the present study, we performed a comprehensive screening of site-specific N-glycopeptides in serum glycoproteins to identify glycopeptide markers for predicting the efficacy of chemotherapy, which is beneficial to personalized treatment. In total, 20 serum samples before and after neoadjuvant chemotherapy (NACT) from 10 LACC patients (NACT response, n=6) and NACT nonresponse, n=4) cases) were analyzed using LC-MS/MS, and 20 sets of mass spectrometry (MS) data were collected using liquid chromatography coupled with high-energy collisional dissociation tandem MS (LC-HCD-MS/MS) for quantitative analysis on the novel software platform, Byos. We also identified differential glycopeptides before and after chemotherapy in chemo-sensitive and chemo-resistant patients.

Results

In the present study, a total of 148 glycoproteins, 496 glycosylation sites and 2279 complete glycopeptides were identified in serum samples of LACC patients. Before and after chemotherapy, there were 13 differentially expressed glycoproteins, 654 differentially expressed glycopeptides and 93 differentially expressed glycosites in the NACT responsive group, whereas there were 18 differentially expressed glycoproteins, 569 differentially expressed glycopeptides and 99 differentially expressed glycosites in the NACT nonresponsive group. After quantitative analysis, 6 of 570 glycopeptides were identified as biomarkers for predicting the sensitivity of neoadjuvant chemotherapy in LACC. The corresponding glycopeptides included MASP1, LUM, ATRN, CO8A, CO8B and CO6. The relative abundances of the six glycopeptides, including MASP1, LUM, ATRN, CO8A, CO8B and CO6, were significantly higher in the NACT-responsive group and were significantly decreased after chemotherapy. High levels of these six glycopeptides may indicate that chemotherapy is effective. Thus, these glycopeptides are expected to serve as biomarkers for predicting the efficacy of neoadjuvant chemotherapy in locally advanced cervical cancer.

Conclusion

The present study revealed that the N-glycopeptide of MASP1, LUM, ATRN, CO8A, CO8B and CO6 may be potential biomarkers for predicting the efficacy of chemotherapy for cervical cancer.

Insight into autophagy in platinum resistance of cancer

Platinum drugs, as a class of widely used chemotherapy agents, frequently appear in the treatment of cancer at different phrases. However, platinum resistance is the major bottleneck of platinum drugs for exerting anti-tumor effect. At present, the mechanism of platinum resistance has been thoroughly explored in terms of drug delivery methods, DNA damage repair function, etc., but it has not yet been translated into an effective weapon for reversing platinum resistance. Recently, autophagy has been proved to be closely related to platinum resistance, and the involved molecular mechanism may provide a new perspective on platinum resistance. The aim of this review is to sort out the studies related to autophagy and platinum resistance, and to focus on summarizing the relevant molecular mechanisms, so as to provide clues for future studies related to autophagy and platinum resistance.

Machine Learning-Assisted Ensemble Analysis for the Prediction of Response to Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer

The clinical benefit of neoadjuvant chemotherapy (NACT) before concurrent chemoradiotherapy (CCRT) vs. adjuvant chemotherapy after CCRT is debated. Non-response to platinum-based NACT is a major contributor to poor prognosis, but there is currently no reliable method for predicting the response to NACT (rNACT) in patients with locally advanced cervical cancer (LACC). In this study we developed a machine learning (ML)-assisted model to accurately predict rNACT. We retrospectively analyzed data on 636 patients diagnosed with stage IB2 to IIA2 cervical cancer at our hospital between January 1, 2010 and December 1, 2020. Five ML-assisted models were developed from candidate clinical features using 2-step estimation methods. Receiver operating characteristic curve (ROC), clinical impact curve, and decision curve analyses were performed to evaluate the robustness and clinical applicability of each model. A total of 30 candidate variables were ultimately included in the rNACT prediction model. The areas under the ROC curve of models constructed using the random forest classifier (RFC), support vector machine, eXtreme gradient boosting, artificial neural network, and decision tree ranged from 0.682 to 0.847. The RFC model had the highest predictive accuracy, which was achieved by incorporating inflammatory factors such as platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, neutrophil-to-albumin ratio, and lymphocyte-to-monocyte ratio. These results demonstrate that the ML-based prediction model developed using the RFC can be used to identify LACC patients who are likely to respond to rNACT, which can guide treatment selection and improve clinical outcomes.

Enhanced Efficacy of Neoadjuvant Chemotherapy with Nab-Paclitaxel and Platinum for Locally Advanced Cervical Cancer

Purpose

We aimed to determine the effect of neoadjuvant chemotherapy consisting of albumin-bound paclitaxel (“nab-paclitaxel”) and platinum (NACT-nPP) in patients with locally advanced cervical cancer (LACC).

Methods

Consecutive patients with newly diagnosed, non-metastatic LACC were recruited retrospectively between October 2016 and June 2020 in our hospital. All patients received concurrent chemoradiotherapy (CCRT) alone or neoadjuvant chemotherapy. We compared the complete response (CR) rate and 2-year progression-free survival (PFS) between patients receiving NACT-nPP and not receiving regimens or other regimens of neoadjuvant chemotherapy.

Results

A total of 195 patients were enrolled (78 in the NACT-nPP group and 117 in the control group). Upon chemoradiotherapy completion, 72 (92.3%) patients in the NACT-nPP group and 96 (82.1%) patients in the other group achieved CR (P = 0.042). For patients with squamous cell carcinoma, the NACT-nPP group had superior 2-year PFS than that of the control group (89.7% vs 74.1%, P = 0.027, HR = 2.486, 95% CI = 1.077–5.739) whereas for adenocarcinoma, 2-year PFS was 37.5% and 36.5%, respectively (P = 0.863). In multivariate analysis, NACT-nPP and stage were independent prognostic factors (P = 0.046 and 0.012, HR = 2.357 and 2.499, 95% CI = 1.016–5.465 and 1.216–4.930, respectively). The acute hematological adverse events above grade 3 were manageable in the NACT-nPP group (46.2%, 36/78), and the rate was lower than that in the control group (55.6%, 65/117).

Conclusion

Compared with CCRT alone, NACT-nPP followed by CCRT could improve the CR rate and 2-year PFS of patients with locally advanced cervical squamous cell carcinoma, and the toxicity was tolerable. NACT-nPP was an independent prognostic factor for 2-year PFS. However, further prospective studies are needed to confirm our results.

Development and Validation of a Nomogram for the Estimation of Response to Platinum-Based Neoadjuvant Chemotherapy in Patients with Locally Advanced Cervical Cancer

Purpose

Non-response to platinum-based neoadjuvant chemotherapy (non-rNACT) reduces the surgical outcomes of patients with locally advanced cervical cancer (LACC). The development of an accurate preoperative method to predict a patient’s response to NACT (rNACT) could help surgeons to manage therapeutic intervention in a more appropriate manner.

Patients and Methods

We recruited a total of 341 consecutive patients who underwent platinum-based NACT followed by radical surgery (RS) at the Hubei Cancer Hospital between January 1, 2010 and April 1, 2020. All patients had been diagnosed with stage Ib2-IIa2 cervical cancer in accordance with the 2009 International Federation of Gynecology and Obstetrics (FIGO) classification system. First, we created a training cohort of patients who underwent NACT+RS (n=239) to develop a nomogram. We then validated the performance of the nomogram in a validation cohort of patients who underwent NACT+RS (n=102). Data analysis was conducted from October 1, 2020. First, we determined overall survival (OS) and progression-free survival (PFS) after NACT+RS. Multivariate logistic regression was then used to identify independent risk factors that were associated with the response to rNACT; these were then incorporated into the nomogram.

Results

The analysis identified several significant differences between the rNACT and non-rNACT groups, including neutrophil–lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), lymphocyte monocyte ratio (LMR), platelet count, and FIGO stage. The performance of the rNACT nomogram score exhibited a robust C-index of 0.76 (95% confidence interval [CI]: 0.65 to 0.87) in the training cohort and high C-index of 0.71 (95% CI: 0.62 to 0.78) in the validation cohort. Clinical impact curves showed that the nomogram had good predictive ability.

Conclusion

We successfully established an accurate and optimized nomogram that could be used preoperatively to predict rNACT in patients with LACC. This model can be used to evaluate the risk of an individual patient experiencing rNACT and therefore facilitate the choice of treatment.