ABSTRACT BACKGROUND We aimed to comprehensively evaluate the immunologic landscape at baseline and upon chemotherapy in cervical cancer. The information should aid ongoing clinical

investigations of checkpoint blockade immunotherapies in this disease setting. METHODS A series of 109 cervical carcinoma patients was retrospectively assayed before and after neoadjuvant

chemotherapy. Tumour-infiltrating immune markers (CD3, CD4, CD8, CD20, CD56, CD68, PD-1, PD-L1) were assessed by immunohistochemistry. RNA sequencing analysis was performed on matched pre-

and post-treatment fresh-frozen tissues. RESULTS At diagnosis, diverse immune cell types including CD20+ B cells, CD3+ T cells, CD56+ natural killer (NK) cells, and CD68+ macrophages were

Neoadjuvant chemotherapy was associated with increased CD4, CD8, CD20, and CD56 signals, most prominently in good responders. Transcriptomic data corroborated the improved anticancer

immunity and identified immunosuppressive CD200 upregulation following chemotherapeutic intervention. CONCLUSIONS A subset of cervical cancer harbours active immune microenvironment, and

chemotherapy treatment may further exert locoregional immunostimulation. Immune checkpoint inhibitors as combination or maintenance therapies warrant future exploration in clinic. SIMILAR

CONTENT BEING VIEWED BY OTHERS SINGLE-CELL RNA-SEQUENCING REVEALS RADIOCHEMOTHERAPY-INDUCED INNATE IMMUNE ACTIVATION AND MHC-II UPREGULATION IN CERVICAL CANCER Article Open access 30 January

2023 LINKING TUMOR IMMUNE INFILTRATE AND SYSTEMIC IMMUNE MEDIATORS TO TREATMENT RESPONSE AND PROGNOSIS IN ADVANCED CERVICAL CANCER Article Open access 19 December 2023 CRUCIAL IMMUNOLOGICAL

ROLES OF THE INVASION FRONT IN INNATE AND ADAPTIVE IMMUNITY IN CERVICAL CANCER Article 29 October 2024 BACKGROUND Cervical cancer is a significant cause of women’s mortality with

approximately 569,847 new cases and 311,365 deaths annually worldwide.1 Currently, patients with advanced cervical cancer have limited therapeutic options. In recent years, extensive

epidemiological, laboratory, and clinical investigations have been undertaken to tackle this life-threatening problem. One notable progression is the ground-breaking discovery of high-risk

human papillomavirus (HPV) as a major aetiological factor for cervical cancer.2 The subsequent prophylactic HPV vaccination and effective screening of precancerous lesions followed by

preventive treatment have yielded a dramatic reduction in the late-stage disease incidence.3,4 Although we envision that cervical cancer will be eventually eliminated with these efforts,

until it can be optimistically accomplished after decades,5 basic scientific advances still need to be made and novel lifesaving medicines are imminently desired to overcome this global

threat of public health.6,7 It has been well established that tumour microenvironment, especially the immune milieu, plays a crucial role in modulating disease progression and response to

anticancer therapies.8,9,10 As expected, cellular and molecular indicators of positive immune activities are typically associated with long-term patient survival, and vice versa.11,12

Indeed, numerous studies have identified certain immune contexture or immunity-related gene signatures as prognostic biomarkers in a wide spectrum of human malignancies.13,14,15,16 Along

similar lines, accumulating data suggest that the baseline immunologic state within tumour lesions determines the clinical outcome following pharmacological interventions, ranging from

conventional chemotherapeutics to targeted compounds.17,18,19 These anticancer agents may in turn trigger immunogenic cell death and alter the composition and phenotype of intratumoural

immune infiltrates.20,21,22 By exerting cytotoxic effects, many anti-neoplastic drugs often have the tendency to stimulate the innate and acquired immune system, thereby facilitating tumour

eradication.23,24,25 In fact, the ultimate therapeutic efficacy as a result of administered regimens sometimes hinges on their capacity to engage functional immune circuitries and restore

immunosurveillance.26,27,28,29 Therefore, malignant cells commonly co-opt multiple evasion mechanisms to avoid immune attack,30,31,32,33 and a rational approach unleashing the

immunoreactivity holds considerable promise for potentially curative remedies, as exemplified by the recent emergence of cancer immunotherapies to reinstate the immunological control of

diverse neoplasms.34,35,36 Hallmarked by HPV-driven carcinogenesis, cervical cancer is presumed to possess immunogenicity by nature.37,38,39 Meanwhile, persistent viral infection could also

induce host immune tolerance, thus leading to a more complicated scenario.40,41 Surprisingly, in-depth characterisation of its immunologic landscape has been rather scanty with only a few

reports focussing on specific cell subsets.42,43,44,45 We reasoned that a more thorough understanding of the immune components and their interrelation with empirical treatments would provide

enormous opportunities for improving patient management and optimising therapeutic protocols. In this study, using immunohistochemical (IHC) staining and RNA sequencing (RNA-seq), we

systematically surveyed various immune cell populations present in different stages of cervical cancer at baseline or upon neoadjuvant chemotherapy (NACT). These integrated analyses allowed

for a critical evaluation of tumour-infiltrating immune profiles and might contribute to the ongoing development of immunomodulatory therapies in cervical cancer. METHODS PATIENT COHORT The

study was conducted in accordance with ethical guidelines of the U.S. Common Rule and was approved by the Ethics Committee of Ren Ji Hospital. Appropriate written informed consent was

obtained from each patient. All patients were treated at the Department of Obstetrics and Gynecology, Ren Ji Hospital, and their clinical records and tissue specimens were retrospectively

retrieved. Formalin-fixed and paraffin-embedded (FFPE) sections were obtained in pathologic examination. For RNA-seq analysis, fresh-frozen tumour tissues were collected during diagnostic

biopsy (pre-chemotherapy) and debulking surgery (post-chemotherapy). A total of 14 patients (28 paired samples) were assayed. Magnetic resonance imaging (MRI) data were provided by the

Department of Radiology, Ren Ji Hospital. Detailed clinical characteristics of the patient cohort are described in Supplementary Table 1. CHEMOTHERAPY RESPONSE EVALUATION The clinical

response to NACT was assessed according to the Response Evaluation Criteria in Solid Tumours. The evaluation was performed by an experienced radiologist (J.C.) on the basis of MRI images

following 1–2 cycles of chemotherapy treatment. A complete response (CR) was defined as the disappearance of the initial lesions. A partial response (PR) was defined as the detection of at

least a 30% reduction in the sum of the longest dimensions of the primary tumours. Progressive disease (PD) was defined as a >20% increase in the sum of the longest dimensions of the

target lesions or the development of new lesions. Stable disease (SD) implied that none of the above applied. Patients with CR or PR were defined as good responders, and patients with SD or

PD were defined as poor responders. IMMUNOHISTOCHEMISTRY IHC was performed on 5-μm-thick FFPE tissue sections. Slides were baked, deparaffinised in xylene, passed through graded alcohols,

and antigen retrieved with 10 mM citrate buffer, pH 6.0 in a steam pressure cooker. Pre-processed tissues were treated with peroxidase block (Dako) to quench endogenous peroxidase activity,

blocked using protein block (Dako), and incubated with primary antibodies (Supplementary Table 2). Slides were then washed in 50 mM Tris-HCl, pH 7.4 and incubated with horseradish

peroxidase-conjugated secondary antibodies. Immunoperoxidase staining was developed using the DAB system according to the manufacturer’s instructions (Dako). Slides were counterstained with

haematoxylin, dehydrated in graded alcohol and xylene, and cover-slipped using mounting solution. IHC STAINING QUANTIFICATION Areas of necrosis or artefacts were ignored. Microscopically,

the cell membrane in the slices was stained. The slides were examined using a bright field microscope and were scored using a four-point scale. First, for progression-free survival (PFS)

survival analysis, the immune cellular staining of each antibody was semi-quantitatively scored as ‘−’ (no or <5% positive cells), ‘+’ (5–25% positive cells), ‘++’ (26–50% positive

cells), and ‘+++’ (>50% positive cells). Both tumour and immune cell staining of programmed death-ligand 1 (PD-L1) were scored. The IHC signals were enumerated in ten random ×20 fields,

and cell counts were normalised to the area of tumour tissues. The samples with staining scores of ‘−’ were considered as the negative group, whereas those with staining scores of ‘+’, ‘++’,

and ‘+++’ were combined into the positive group. Second, in order to perform correlation analysis and quantitative comparison before and after NACT accurately, the slides were also scanned

with an Aperio ScanScope system (Leica Biosystems) and quantified using the Aperio ImageScope software v12.1 with Positive Pixel Count v9 (PPCv9) algorithm for statistical analysis. RNA-SEQ

AND ANALYSIS We performed RNA-seq analysis on 14 patients (28 samples) with matched pre- and post-chemotherapy fresh-frozen tissues. Total RNA was extracted from shavings of fresh-frozen

specimens using the RNeasy Plus Kit (Qiagen) according to the manufacturer’s protocol. RNA purity and integrity were assessed by the NanoPhotometer spectrophotometer (Implen) and RNA Nano

6000 Assay Kit on Bioanalyzer 2100 system (Agilent Technologies), respectively. Total RNAs with RNA Integrity Number of >8 were subjected to next-generation sequencing. Total amount of 3 

µg RNA for each sample was used as input materials for library preparation with the NEBNext Ultra Directional RNA Library Prep Kit (NEB). The index-coded libraries were clustered on a cBot

Cluster Generation System using the TreSeq PE Cluster Kit v3-cBot-HS (Illumina) and sequenced on an Illumina Hiseq X Ten platform to generate 125 bp paired-end reads (Novogene). Clean data

were obtained from FastQ raw data by removing adapter, poly-N sequences, and low-quality reads. All the downstream analyses were based on the clean data with high quality. Index of the

reference genome was built using Bowtie v2.0.6 and paired-end clean reads were aligned to the reference genome (Ensembl hg38 human genome) using TopHat v2.0.9.46 The mapped reads of each

sample were assembled by Cufflinks (v2.1.1) in a reference-based approach.47 Differential expression analysis was performed using Cuffdiff (v2.1.1). P-values were adjusted using the

Benjamini–Hochberg procedure for controlling the false discovery rate. Genes with an adjusted _P_ value of <0.05 were considered differentially expressed. The sequencing data have been

deposited in the NCBI BioProject database (http://www.ncbi.nlm.nih.gov/bioproject/) under the accession number SRP173984. STATISTICAL ANALYSIS Statistical analyses were performed with the R

language and Graphpad Prism 6. Unsupervised hierarchical clustering was conducted to define the immune subtypes based on the evaluated markers. Pearson correlation analysis was used to test

the associations between different immune measurements. Cumulative survival rate was calculated by the Kaplan–Meier method and analysed by log-rank test. Cox proportional models were used to

determine the hazard ratio that represents the relative risk of events among patients in the different groups. Gene ontology and pathway analyses were performed using Metascape

(http://metascape.org).48 Single sample gene set enrichment analysis implemented in the Bioconductor ‘GSVA’ package was applied to generate compound scores for the indicated gene

signatures.49 CIBERSORT was employed to estimate the relative abundance of diverse immune cell infiltrates from gene expression profiles.50 Antigen receptor repertoire present in bulk

RNA-seq data was inferred by MiXCR.51 Comparisons between two conditions were based on two-sided Student’s _t_ test. _P_ values of <0.05 were judged to be statistically significant.

RESULTS PATIENT CHARACTERISTICS The study cohort contained 109 cases of cervical cancer with high-quality FFPE tissues and clinicopathological information available (Supplementary Table 1).

The median age of the patients was 52 years (range, 25–83 years). The histological diagnosis was mainly squamous cell carcinoma (89.9%) and adenocarcinoma (9.2%) of different International

Federation of Gynecology and Obstetrics stages (IA–IVA). Forty (36.7%) and sixty-nine (63.3%) subjects received upfront radical hysterectomy and NACT followed by surgery or

chemoradiotherapy, respectively (Supplementary Fig. 1a). We were able to obtain 92 treatment-naive samples and 60 chemo-exposed specimens from the diagnostic biopsies or surgical procedures,

among which 43 pairs were matched pre- and post-NACT tissues. In total, 152 (92 treatment-naive and 60 chemo-exposed) FFPE blocks underwent IHC examination, and 28 fresh-frozen tumours (14

pre-NACT and 14 post-NACT) from the NACT group were subjected to RNA-seq analysis (RJCC1–14, all squamous cell carcinomas). PATTERNS OF BASELINE IMMUNE INFILTRATES IN CERVICAL CANCER To

systematically analyse the immune makeup of cervical cancer, CIBERSORT,50 a computational method for inferring the relative abundance of diverse cell infiltrates from bulk tumour

transcriptomes, was initially conducted on the gene expression data (RJCC1–14, 28 data sets) profiled by RNA-seq. This framework pinpointed that the major representative immune cell types

were B cells, T cells, natural killer (NK) cells, and macrophages (Supplementary Fig. 1b). Based on these findings, we assembled a panel of monoclonal antibodies to probe each

subset-specific marker, as well as immune checkpoint molecules including programmed death-1 (PD-1) and PD-L1 (Supplementary Table 2). These eight immunologic parameters displayed divergent

positive staining ratios in the 92 untreated samples. We observed CD3+ pan T cells (66.3%), CD4+ helper T cells (47.4%), CD20+ B cells (41.1%), and CD68+ macrophages (75.8%) in a prevalent

population of cervical tumours, whereas CD8+ cytotoxic T cells (32.6%), CD56+ NK cells (30.5%), PD-1 (15.8%), and PD-L1 (31.6%) signals were restricted to a smaller fraction of cancer

patients (Fig. 1a). While most immune markers were comparable between cervical adenocarcinoma and squamous cell carcinoma, histotype-specific CD20 and CD56 positivity was noted

(Supplementary Fig. 2). In order to better understand the complex immune characteristics in cervical cancer, we quantified the immune stains and assessed their interrelationships by

analysing pairwise correlation between the evaluated variables. Unsupervised hierarchical clustering of Pearson correlation coefficients (_R_) was visualised in a heatmap, which identified a

dominant array of co-modulated markers, including CD3, CD4, CD8, CD20, CD68, PD-1, and PD-L1 (Fig. 1b). There was a statistically significant positive correlation between PD-L1 intensity

and CD3+, CD4+, or CD8+ tumour-infiltrating lymphocytes (TILs) (Fig. 1c), consistent with the known role of T cell-derived cytotoxicity as a driver of PD-L1 expression.52 Among the 29 cases

(31.6%) showing PD-L1 staining, PD-L1 was mostly expressed on tumour cell surface (29.5%) and only sporadically detected in immune cells (2.1%; Fig. 1d). Taken together, these results

indicated that cervical cancer at baseline contained both innate and adaptive immune cells, as well as immune checkpoint expression within the tumour microenvironment. ASSOCIATION OF IMMUNE

INFILTRATES WITH PATIENT PROGNOSIS We explored the prognostic impact of baseline immune markers in cervical cancer and found CD8+ T cell infiltration as the most promising candidate to be

associated with beneficial clinical outcome regardless of neoadjuvant treatment (Supplementary Fig. 3a). We further considered the combination of immunologic features and performed

unsupervised hierarchical clustering of eight attributes. Four subgroups were revealed and arbitrarily designated as cluster 1 (16.8%), cluster 2 (37.9%), cluster 3 (26.3%), and cluster 4

(18.9%) (Fig. 2a). Cluster 1 (termed ‘immuno-active’) exhibited marked positivity for nearly all IHC markers other than CD56 and PD-1, hence resembling typical immunoreactive tumours (Fig. 

2b). Cluster 2 (termed ‘immuno-medial’) showed moderate levels of immune contents (Fig. 2c). Cluster 3 (termed ‘immuno-deficient’) represented the immunologically inert prototype with low

immune cell densities (Fig. 2d). Cluster 4 (termed ‘immuno-NK’) was uniquely defined by prominent CD56+ NK cells (Fig. 2e). We found that the ‘immuno-deficient’ group (cluster 3) had

relatively shorter PFS than the ‘immuno-active’ group (cluster 1), and the ‘immuno-medial’ group (cluster 2) displayed intermediate risk of relapse (Fig. 2f). Interestingly, patients

categorised as ‘immuno-NK’ (cluster 4) demonstrated a PFS advantage compared to those in the ‘immuno-deficient’ and ‘immuno-medial’ classes (Fig. 2f). Of note, we discovered tertiary

lymphoid structures (TLSs) characterised by ectopic intratumoural aggregates of B and T lymphocytes (Fig. 2g and Supplementary Fig. 1b), which preferentially existed in the ‘immuno-active’

tumours (45.8%) and tended to correlate with improved PFS (Fig. 2h). Therefore, the magnitude and composition of baseline immune infiltrates aided the stratification of cervical cancer

patients into distinct molecular subtypes with prognostic relevance. IMMUNE AUGMENTATION UPON NACT Sixty-nine patients with locally advanced disease were first dosed with primary

chemotherapeutic regimens and subsequently evaluated to further receive surgical resection (62 patients) or chemoradiotherapy (7 patients). This neoadjuvant setting, although controversial,6

offered an unprecedented opportunity to investigate the potential impact of conventional systemic intervention on tumour microenvironment for rational combination with immunotherapeutics

and to explore the predictive determinants of chemosensitivity for patient-tailored medicine. To this end, we collected 60 specimens from debulking surgery after platinum-based doublets

(mostly cisplatin) and carried out IHC assessment using the same aforementioned antibody panel. Compared to the baseline (92 samples), cervical cancer following chemotherapy (60 samples)

experienced a significant reduction in Ki67 and PD-L1 positivity (Fig. 3a), in line with drug-invoked tumour cell death. By contrast, the densities of multiple immune markers, including CD4,

CD8, CD20, CD56, and PD-1, were evidently increased in chemo-treated samples (Fig. 3a). Treatment-conferred enrichment of CD4+, CD8+, CD20+, and CD56+ TIL was verified by performing paired

analysis (Fig. 3b) and inspecting representative IHC images (Fig. 3c) in the 43 cases with matched pre- and post-NACT sections. Although immunomodulatory effects of NACT were considerably

variable among these 43 individuals, an expansion of each immune cell population was noted in >50% of the patients without exception (Supplementary Fig. 4a). Of particular relevance, we

also observed CD14+ myeloid cell depletion by NACT (Supplementary Fig. 4b), which was shown to foster robust T cell reactivity in HPV16-based vaccination.53,54 In addition, TLSs were

markedly induced and arose de novo in some cases (Supplementary Fig. 4c). These data suggested that NACT fostered pronounced immune augmentation in cervical cancer. PATTERNS OF IMMUNE

AUGMENTATION UPON NACT We sought to delineate the overall patterns of immunostimulation by NACT in more detail. Analogous to the earlier immune profiles, the NACT cohort with paired samples

(43 patients) could be hierarchically divided into ‘immuno-active’, ‘immuno-medial’, ‘immuno-deficient’, and ‘immuno-NK’ subtypes as well. The most striking TIL accumulation occurred in the

initially classified ‘immuno-deficient’ tumours (Fig. 4a). Chemotherapeutic-elicited immunogenic phenotype was also manifested by frequent gain of CD56+ NK cells across all four molecular

clusters (Fig. 4a). We further compared TIL levels with respect to the clinical outcome by segregating NACT-treated patients (65 out of 69 evaluable) into good responders (with CR or PR) and

poor responders (with SD or PD) (Supplementary Fig. 5). As expected, 44 good responders exhibited better PFS than 21 poor responders (Fig. 4b). Of interest, decreased Ki67 and PD-L1

signals, as well as intensified CD4, CD8, CD20, CD56, and PD-1 staining, were specifically observed in good responders (Fig. 4c) but not in poor responders (Fig. 4d). Although the limited

number of cases and events did not allow for definitive assessment on the predictive value of immune augmentation, elevated abundance of diverse lymphatic cell populations, similar to the

TIL-enriched status regardless of medication, tended to be positively associated with chemotherapy response (Supplementary Fig. 6). Collectively, the immunomodulatory action of NACT was

affected by both baseline immunity and therapeutic efficacy. EVALUATION OF IMMUNOLOGIC PROPERTIES WITH RNA-SEQ We leveraged the RNA-seq data of 14 fresh-frozen sample pairs (RJCC1–14) to

validate the relationship between antitumour immunity and neoadjuvant treatment. NACT caused discrepant changes of gene expression in each patient and, across the cohort, resulted in 45

upregulated and 4 downregulated transcripts (Fig. 5a and Supplementary Fig. 7). Gene ontology and pathway analyses of differentially expressed genes pinpointed multiple significantly altered

modules related to immune activation upon chemotherapy, i.e. ‘TNFA signalling via NFKB’ and ‘inflammatory response’ (Fig. 5b). We conducted gene set variation analysis (GSVA) with

predefined transcriptional signatures for a range of biological processes and found that cell proliferation was indeed impaired, whereas relative amounts of CD8+ T cells, NK cells, and mast

cells were increased following NACT (Fig. 5c). In addition, by specifically analysing various immune checkpoints (Supplementary Fig. 8), we identified a significant upregulation of the

immunosuppressive CD200 molecule (Fig. 5d), which might serve as a potential immunotherapeutic target in chemo-treated cervical cancer. CIBERSORT algorithm confirmed the enlarged fractions

of CD4+ and CD8+ T cell subsets in the majority of residual lesions (Fig. 5e); on the contrary, there were relatively fewer remaining macrophages and T regulatory cells, both considered

negative mediators of immune function. Finally, the deep transcriptome sequencing enabled computational inference of antigen receptor diversities reflected by T cell receptor and

immunoglobulin repertoires using the MiXCR pipeline.51 More complementarity determining region 3 clonotypes were extracted from chemo-exposed tumours in 10 out of 14 sequenced subjects (Fig.

 5f), implying enhanced lymphocyte infiltration. We concluded that the RNA-seq experiment substantially verified our IHC findings of chemotherapy-coupled immunostimulation in cervical

cancer. DISCUSSION In this study, by integrating IHC and RNA-seq analysis, we presented a rational approach for detailed interrogation of immune microenvironment in a large series of

cervical cancer. Our data revealed divergent baseline immunologic states that stratified patients into distinctive prognostic subgroups. Brief exposure and clinical response to NACT

seemingly incited a favourable reshaping of antitumour immunity against cervical carcinoma. These findings not only hold promise to better understand the impact of tumour–immune interactions

on disease behaviour and management but also provide the foundation to investigate synergistic treatment options of combining conventional chemotherapy with immunotherapeutic agents. We

employed a robust in silico deconvolution framework to estimate the immune constituents from bulk gene expression profiles,50 which indicated the highest degree of infiltrating B cells, T

cells, NK cells, and macrophages in cervical tumours. It is noteworthy that the computational measurements were at best approximate, and a definitive cellular composition and abundance can

be conceivably resolved using single-cell RNA-seq technology in the future.55,56 Nevertheless, these prevalent TIL populations were independently validated by immunostainings and

collectively segregated samples into four molecular subtypes. As with numerous other cancer types,57 cervical malignancies were vastly heterogeneous in the breadth of immune cell

infiltration. Remarkably, we found that B cells and T cells sporadically formed into TLSs, which were reported to play a direct role in the priming of antitumour immunity.58,59,60,61,62 In

addition, a unique subset of patients was revealed to contain disproportionate intratumoural NK cells and has exceptionally inferior risk of disease progression compared to other molecular

subtypes. This observation accords with the notion that NK cells are key to cancer immunosurveillance as both cytolytic effectors of the innate immune system and emerging regulators of the

adaptive immune cascade.63,64 Taken together, our in-depth characterisation of the immune portraits reinforced the immunogenic nature of virally driven cervical cancer. Chemotherapy,

including the mainstay cisplatin in cervical cancer, has traditionally been considered largely immunosuppressive due to its direct haematologic toxicity. However, such view is challenged by

cumulative evidence showing that it can enhance certain facets of locoregional immune response in a variety of human cancers.21,22,23,29,65 Along this line, we discovered that preoperative

chemotherapy indeed converted cervical lesion into a site permissive for antitumour immunity, as exemplified by selective enrichment of CD4+, CD8+, CD20+, and CD56+ TIL. The molecular

mechanisms underlying the inflammatory effects of cytotoxic chemotherapeutics have been predominantly attributed to the drug-evoked immunogenic cell death, involving for instance surface

calreticulin exposure,66 HMGB1 secretion,67 autophagic ATP release,68 NLRP3 inflammasome activation,69 cytokine production,70 and instigation of antigen-presenting dendritic cells.71

Alternatively, recent work showed that standard chemotherapy was able to reduce immunosuppressive myeloid cells and enhance T cell responses to therapeutic HPV16 vaccine in cervical

cancer.53,54 Of note, myriad preclinical and clinical studies have also unveiled differential immunostimulatory capacities of different chemotherapeutic agents.72,73 Given the pleiotropic

functions of chemotherapy, additional work is deserved to fully elucidate the mechanistic determinants responsible for the augmenting immune activities. Although ongoing trials with immune

checkpoint inhibitors in cervical cancer have shown early promising outcome, clinical responses are generally modest and variable.74 A disappointing 3% objective response rate (ORR) was

observed in a Phase 1/2 trial of 42 women who received ipilimumab (anti-CTLA-4) as monotherapy.75 In KEYNOTE-028 with pembrolizumab (anti-PD-1), ORR was 17% and median duration of response

was merely 5.4 months.76 Most recently, the KEYNOTE-158 Phase 2 basket trial presented an interim ORR of 12.2%, leading to the accelerated approval of pembrolizumab in advanced

PD-L1-positive cervical cancer.77 Overall, the potency of immune-based regimens is limited in unselected patient populations and should be tailored according to clinicopathological or

molecular attributes. Illuminated by current study, we propose the following paradigm shift toward precision immunotherapy for cervical cancer. The ‘immuno-active’ tumours may experience

spontaneous immunogenicity considering pronounced basal lymphocyte infiltration and PD-L1 expression and are likely poised to benefit from immunomodulatory medicine regardless of

chemotherapeutic education. For the ‘immuno-medial’ or ‘immuno-active’ subtypes, combined or induction chemotherapy is a plausible option to provoke iatrogenic immunogenicity. The

‘immuno-NK’ cluster illustrates an opportunity for pharmacological inhibition of NK cell checkpoints.78 Therefore, an improved understanding of the immune status at baseline and upon

specific treatments could yield valuable insights into more optimised and efficacious therapeutic modalities of cervical cancer. Several limitations of this exploratory study have to be

acknowledged. First, our investigations were retrospective in nature with potential biases owing to missing clinical records and unpredictable tissue availability. Second, these preliminary

results stemmed from one patient cohort in a single institution without internal and external validation data sets. Third, we mainly relied on conventional protein markers to define immune

cell types and ideally the corroborative RNA-seq analyses should have included a larger number of subjects. Finally, the prognostic and predictive significance of chemo-induced TIL

remodelling was underpowered to determine and future efforts with adequate sample size are warranted in this respect. CONCLUSIONS In summary, we provided for the first time a comprehensive

snapshot of baseline immunologic features within cervical tumour microenvironment and further uncovered the association between NACT effects and an immunostimulatory phenotype. Expanded

studies in the prospective setting are required to verify these findings, which may have clinical implications for tailoring immune-based treatment in women with cervical cancer. REFERENCES

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cancer immunotherapy. _Trends Immunol._ 40, 142–158 (2019). Article  CAS  PubMed  Google Scholar  Download references ACKNOWLEDGEMENTS The authors would like to thank Department of Pathology

and Biobank from Ren Ji Hospital for valuable assistance on coordinating IHC evaluation and preserving patient specimens. AUTHOR INFORMATION Author notes * These authors contributed

equally: Yi Zhang, Minhua Yu, Ying Jing AUTHORS AND AFFILIATIONS * State Key Laboratory of Oncogenes and Related Genes, Department of Obstetrics and Gynecology, Ren Ji Hospital, School of

Medicine, Shanghai Jiao Tong University, Shanghai, China Yi Zhang, Minhua Yu, Ying Jing, Lin Cheng, Haijiao Lu, Wenjing Wang, Weihua Lou, Lihua Qiu, Xia Yin, Guanglei Zhuang & Wen Di *

Shanghai Key Laboratory of Gynecologic Oncology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China Yi Zhang, Minhua Yu, Ying Jing, Lin Cheng, Haijiao Lu, 

Wenjing Wang, Weihua Lou, Lihua Qiu, Xia Yin, Guanglei Zhuang & Wen Di * Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

Jiejun Cheng * State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China Caiyan

Zhang & Mei-Chun Cai * Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China Jie Wu * Interdisciplinary Research Center on Biology and Chemistry,

Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China Li Tan * Department of Gynecologic Oncology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University,

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Scholar CONTRIBUTIONS Conception and design: X.Y., G.Z.; development of method: M.-C.C., L.T.; acquisition of data: Y.J., J.C., C.Z., L.C., H.L., M.-C.C., J.W., W.W.; analysis and

interpretation of data: Y.Z., M.Y., W.L., L.Q., H.L.; writing, review, and/or revision of manuscript: Y.Z., G.Z., W.D.; administrative, technical, or material support: W.L., L.Q., H.L.;

study supervision and approval of final version: W.D. All authors read and approved the final manuscript. CORRESPONDING AUTHORS Correspondence to Xia Yin, Guanglei Zhuang or Wen Di. ETHICS

DECLARATIONS ETHICS APPROVAL AND CONSENT TO PARTICIPATE Patient samples were obtained with informed consent at Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University. Studies

were performed under protocols approved by Ethics Committee of Ren Ji Hospital. Studies were performed in accordance with the Declaration of Helsinki. DATA AVAILABILITY All reagents used in

this study were commercially available. The RNA sequencing data have been deposited in NCBI BioProject database (http://www.ncbi.nlm.nih.gov/bioproject/) under the accession number

SRP173984. COMPETING INTERESTS The authors declare no competing interests. FUNDING INFORMATION This work was supported by the National Natural Science Foundation of China (81672714 and

81922047 to G.Z., 81772770 to W.D.); National Key Research and Development Program (863) of China (2016YFC1302900 to W.D.); National Program on Key Basic Research Project of China

(2016YFA0501900 and 2016YFA0501904 to L.T.); the Shanghai Municipal Key Clinical Specialty and the Program of Shanghai Hospital Development Center (16CR2001A to W.D.); the grants from

Shanghai Jiao Tong University School of Medicine (DLY201505 to W.D., YG2016MS51 to X.Y.); Doctoral Innovation Fund of Shanghai Jiao Tong University School of Medicine (CBXJ201805 to Y.Z.);

Shanghai Pujiang Program (17PJ1410700 to L.T.); Shanghai Municipal Commission of Health and Family Planning (2017ZZ02016 and ZY(2018-2020)-FWTX-3006 to W.D., 20174Y0043 to M.-C.C.,

20174Y0189 to Y.J.); and the grants from Science and Technology Commission of Shanghai Municipality (18441904800 to W.D., 16140904401 to X.Y.). ADDITIONAL INFORMATION NOTE This work is

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ARTICLE Zhang, Y., Yu, M., Jing, Y. _et al._ Baseline immunity and impact of chemotherapy on immune microenvironment in cervical cancer. _Br J Cancer_ 124, 414–424 (2021).

https://doi.org/10.1038/s41416-020-01123-w Download citation * Received: 04 April 2020 * Revised: 01 October 2020 * Accepted: 02 October 2020 * Published: 22 October 2020 * Issue Date: 19

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