Article Text

Download PDFPDF
Pathologic response to neoadjuvant chemotherapy in advanced ovarian cancer: utility of a scoring system to predict outcomes
  1. Camilla Nero1,
  2. Anna Fagotti1,
  3. Gian Franco Zannoni2,
  4. Eleonora Palluzzi1,
  5. Giovanni Scambia1 and
  6. Marco Petrillo3
  1. 1 Dipartimento Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Ginecologia Oncologica, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Roma, Italia
  2. 2 Dipartimento Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Gineco-patologia e Patologia Mammaria, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Roma, Italia
  3. 3 Universita degli Studi di Sassari Facolta di Medicina e Chirurgia, Sassari, Italia
  1. Correspondence to Dr Camilla Nero, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome 00168, Italy; camillanero{at}gmail.com

Abstract

Background Growing evidence supports the role of neoadjuvant chemotherapy in patients with advanced epithelial ovarian cancer. Currently, there is no shared histopathologic scoring system to assess pathologic response in the specimens obtained at interval surgery after neoadjuvant chemotherapy This review aims to summarize the literature on pathologic response, focusing on proposed scoring systems.

Methods The systematic review was conducted according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, focusing on the definition of pathologic response, its prognostic value, possible predictors, and future implications. Eighteen manuscripts focusing on pathologic response in epithelial ovarian cancer were selected for analysis.

Results Overall, eight histopathologic scoring systems to evaluate pathologic response have been proposed. There are currently no available markers (serum, radiological, genomic) to select which patients could achieve the highest benefit from neoadjuvant chemotherapy experiencing a complete pathologic response. A three-tier scoring system (CRS) based on omental assessment and which classifies the response to neoadjuvant chemotherapy has been validated in external cohorts of epithelial ovarian cancer. This scoring system demonstrated adequate interobserver reproducibility. Data is limited on the pathologic complete response rate changes according to chemotherapy regimen.

Conclusions A histopathologic scoring system endowed with prognostic value could be helpful in personalizing the treatment decision in patients with epithelial ovarian cancer.

  • ovarian cancer
  • neoadjuvant chemotherapy
  • pathologic response
  • interval debulking surgery

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Introduction

Despite advances in surgical care and personalized medical approaches, epithelial ovarian cancer remains the most lethal gynecological malignancy, with only a small survival improvement achieved in the past decades.1 Furthermore, approximately 70% of women with epithelial ovarian cancer are diagnosed with advanced disease, thus leading to a challenge in proposing optimal therapy. In fact, evidence from retrospective series have demonstrated that complete resection of all macroscopic disease represents the strongest predictor of clinical outcome,2 3 and, therefore, primary debulking surgery is considered by many as the standard of care in women with advanced disease.4

In at least 20% of epithelial ovarian cancer patients optimal cytoreduction cannot be achieved.5–7 Therefore, following the results of three large randomized phase III clinical trials (EORTC, CHORUS, and SCORPION), neoadjuvant chemotherapy has been progressively introduced in the management of patients with advanced disease for whom complete primary surgery is not feasible.5–7 In this context, one of the main concerns regarding neoadjuvant therapy is the low survival rates reported in these prospective clinical trials (median progression-free survival, 12 months).5 6 However, in the very small population of women having a pathologic complete response to neoadjuvant therapy (7%–8%) of the entire population, prognosis appears more encouraging, with progression-free and overall survival approaching 18–36 and 45–72 months, respectively.8–11 As a consequence, pathologic complete response to neoadjuvant therapy, as for other malignancies (breast, cervical, rectal, and lung cancer), is clearly emerging as a powerful surrogate endpoint of efficacy. This stance was recently emphasized in the SGO position statement.12 However, there is still no uniform consensus regarding a histopathological grading system to assess response to neoadjuvant therapy.

This study aims to summarize the current literature analyzing the scoring systems to assess pathologic complete response to neoadjuvant therapy, as well as the prognostic role and predictors of such scoring systems in women with advanced epithelial ovarian cancer.

Methods

The systematic review was conducted according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. A literature search of the PubMed, MEDLINE, and EMBASE electronic databases was performed using the following terms: ‘complete pathologic response’ OR ‘pathologic response’ AND ‘ovarian cancer’. All types of articles were included in the systematic review, with the exception of case reports and commentaries. The authors evaluated abstracts for all studies retrieved, identifying study biases, as well as quality of data.

In particular case reports, commentaries, and any reference dealing with other cancers have been excluded. We included in the final review only studies reporting histopathologic data in response to neoadjuvant chemotherapy (Figure 1).

Figure 1

Consort diagram of the systematic review process.

Results

Assessing a pathologic response: histopathologic score

The clinical response to neoadjuvant therapy is routinely evaluated through a combination of serum CA125 and CT scan using RECIST and RUSTIN criteria.13 14 Pathologic response to neoadjuvant chemotherapy using several scoring systems has been proposed, but a widely accepted tool is not routinely recommended or recognized (Table 1). In a study by Sassen et al,8 the authors described three categories of pathologic response based on nine histologic features of tumor regression (presence of fibrosis, necrosis, inflammatory cell infiltrates, foamy macrophages, enlarged/giant tumor cells, isolated psammoma bodies, hemosiderin, giant cells of foreign-body type, and pattern of tumor infiltration), the pattern and extent of tumor infiltration and the size of the largest tumor focus. In 2009, Ferron et al15 classified 58 patients with epithelial ovarian cancer treated with neoadjuvant chemotherapy followed by interval debulking surgery into three groups according to the partial response assessed in the peritoneum and nodes.

Table 1

Review of published papers on pathologic response and NACT in advanced EOC

  • Group 1: patients with no histological residual disease in the peritoneum or nodes,

  • Group 2: patients with persistent residual disease but exhibiting histological signs of chemo activity: low or moderate mitotic index; necrosis >50%; and fibrosis >50%.

  • Group 3: patients with at least one site exhibiting persistently 'active' cells defined as a high mitotic index or necrosis <50%.

In 2011, Wang et al described cytologic/histologic changes after neoadjuvant chemotherapy in 48 paired cases with both pre- and post- neoadjuvant chemotherapy samples.16 Fibrosis and necrosis were inversely related, hemorrhage and cystic changes were common, and scattered single large cells with vacuolated cytoplasm were seen in all post-chemotherapy cases. Cancer cells commonly showed large hyperchromatic bizarre nuclei with coarse chromatin clumping and multinucleated tumor giant cells were noted in nearly half of cases. However, despite this interesting description of histological features after neoadjuvant chemotherapy, the authors did not elaborate a grading scale.16 In 2012, Samrao et al described the morphological effects of chemotherapy on epithelial ovarian cancer, to evaluate surgical specimens in 67 patients after neoadjuvant chemotherapy.17–19 Four parameters were considered for the assessment on the primary tumor site: fibrosis, necrosis, percentage of residual tumor, and inflammation with grading cutoffs chosen on the basis of previous studies, mainly on esophageal and pancreatic cancers. A Japanese group instead used a 4-grade scale shaped by the Japanese breast cancer 6-grade scale and based on the degree of disappearance of cancer cells, displacement by necrotic and fibrotic tissue, and tumor-induced inflammation of all resected specimens at the time of interval surgery, to retrospectively assess therapeutic response to neoadjuvant chemotherapy in 124 patients with epithelial ovarian cancer.10

Similarly, another Japanese group, in 2017, categorized pathological outcomes of 68 patients undergoing IDS after neoadjuvant dose-dense weekly paclitaxel and carboplatin into four grades:

  • Grade 1: most tumor cells appeared to be viable, however degenerated tumor cells were scattered and more than half of tumor cells appeared to be degenerated.

  • Grade 2a: most tumor cells had disappeared, whereas the remaining tumor cells were vacuolated or degenerated.

  • Grade 2b: numerous psammoma bodies and small numbers of viable tumor cells were observed.

  • Grade 3: small aggregations of macrophages were seen.

The pathological assessment included all surgical specimens derived by IDS, including those from the adnexa and omentum.20

In 2014, Petrillo et al11 proposed a classification based on three categories of pR evaluating 322 EOC:

  • cPR in cases with no residual neoplastic cells in all the surgical specimens, including the adnexa.

  • Microscopic-pathologic response (micro-PR) in cases without macroscopic lesions but with microscopic foci (maximum diameter ≤3 mm).

  • Macroscopic-pathologic response (macro-PR) in all cases with a persistent macroscopic site of disease after NACT.

A similar classification was used by Liang et al21 to retrospectively evaluate the pathologic response in 57 patients treated with epithelial ovarian cancer treated with neoadjuvant chemotherapy and interval surgery using the following classification:

  • complete with no residual disease (cPR)

  • microscopic (microPR)

  • macroscopic (macroPR).

Unfortunately, the heterogeneity in all the proposed parameters and scoring criteria, and the absence of an independent validation or a test for reproducibility has prevented these approaches to be adopted in practice. In 2015, a three-tier scoring system (CRS) was developed and then independently validated in 71 patients.22 It is based on omental assessment and classifies the response to neoadjuvant chemotherapy according to three tiers. CRS 1 indicates no or minimal tumor response; mainly viable tumor with no or minimal regression-associated fibroinflammatory changes, limited to a few foci; and cases in which it is difficult to decide between regression and tumor-associated desmoplasia or inflammatory cell infiltration. CRS 2 indicates appreciable tumor response amid viable tumor that is readily identifiable; multifocal or diffuse regression-associated fibroinflammatory changes with viable tumor in sheets, streaks, or nodules; and extensive regression-associated fibroinflammatory changes with multifocal residual tumor, which is easily identifiable. CRS 3 indicates complete or near-complete response with no residual tumor; minimal irregularly scattered tumor foci seen as individual cells, cell groups, or nodules up to 2 mm maximum size; mainly regression-associated fibroinflammatory changes; and no or very little residual tumor in the complete absence of any inflammatory response. It is advisable to record whether 'no residual tumor' or 'microscopic residual tumor' is present. Regression-associated fibro-inflammatory changes consist of fibrosis associated with macrophages, including foam cells, mixed inflammatory cells, and psammoma bodies, as distinguished from tumor-related inflammation or desmoplasia.

This scoring system demonstrated adequate interobserver reproducibility (kappa, 0.75) and was included in the International Collaboration on Cancer Reporting (ICCR) and the College of American Pathologists (CAP) guidelines for histologic reporting of ovarian carcinoma in 2015 and 2016 respectively.23–25 Finally, the CRS system has been successfully validated in external cohorts of epithelial ovarian cancer.26–29

Prognostic value of pathologic response to neoadjuvant chemotherapy

Patients with minimal or no residual invasive tumor usually have longer survival times.30–32 Sassen et al8 found that the residual tumor size was the only criterion that correlated with overall survival. Patients with no residual tumor (4%), scattered solitary tumor cells, or residual tumor 5 mm or less (10%), had a significantly longer median overall survival (45.6 vs 27.3 months, P=0.02). No other histopathologic regression criterion emerged as significant for prediction of overall survival. Using Sassen’s histological criteria, a Canadian group found that a high pathological tumor response score was the only significant predictor of time to disease-related death (84 vs 31.2 months).9 Ferron et al found that in 58 patients with no residual macroscopic disease after interval surgery, eight belonged to group 1, 14 to group 2, and 36 to group 3 with a 3-year event-free survival of 63%, 12%, and 19% respectively (P=0.02).15 However, univariate analysis demonstrated no influence of histological response on overall survival (3-year overall survival in group 1 88%, group 2 45%, and group 3 62%, P=0.21). The authors concluded that, in their limited series, the degree of the pathologic response has a limited impact on survival following complete interval debulking surgery.15

Likewise, in the retrospective analysis of 124 EOC patients after NACT published by Muraji et al, pR to NACT, as well as clinical stage and residual disease, was shown to be significantly correlated to overall survival (undefined vs 42 vs 37 vs 28 months). A pCR (grade 3) was achieved in 8.9% of cases and a good pR with degenerative change in more than two-thirds of cancer cells (grade 2) in 49.2%.10

Moreover, among patients who achieved a residual disease of <1 cm at IDS, the size of the viable tumor in the operative specimens was inversely correlated with longer progression-free survival and overall survival. In this specific cohort of women, 41.9% of patients had a Grade 0–1 showing significantly worse survivals compared with Grade 2–3. In addition, patients with grade 0–1 were associated with an increased risk of platinum resistance defined as relapse within 6 months.12

Similar results were published by Ebata et al, showing that a pR of grades 2b and 3 predicted a good prognosis after neoadjuvant dose-dense weekly paclitaxel and carboplatin.20 Of the 68 patients, 10.3% were classified as grade 1, 16.2% as grade 2a, 67.7% as grade 2b, and 5.9% as grade 3 with pCR. The median progression-free survival was 18 months in patients with grades 2b or 3,and 15.8 months in those with grades 1 or 2a (P=0.019). Given the low incidence of pCR, the authors believed it may be suitable to combine pCR and near pCR (defined as grade 2b in their study) to estimate prognosis based on pR.20

Unlike what would be expected, especially given the evidence on other cancers and what we have seen so far, in Samrao et al's paper, residual tumor failed to show any significant value in disease outcome either by itself or in combination with other parameters.17 However, this result must be attributed to the site of pathological assessment, the ovaries alone, not including the entire cytoreduction specimen.17

Also in Petrillo et al's paper, the analysis of 322 EOC patients submitted to NACT and IDS documented a significant association between pCR and longer duration of progression-free survival and overall survival, in particular the authors documented a median progression-free survival of 36 months in the pCR group, 16 months in the micro-pR, and 13 months in the macro-pR groups (P=0.001).11 pCR was observed in 6.5% of all patients, while micro-pR and macro-pR were documented in 32.3% and 61.2% patients, respectively. Moreover, the survival analysis including only patients with no residual disease after IDS (73%), confirmed a statistically significant longer longer progression-free survival (pCR, 36 months vs micro-pR, 16 months vs macro-pR, 13 months, P=0.001) and overall survival (pCR, 72 months vs micro-pR, 38 months vs macro-pR, 29 months, P=0.018) in patients showing pCR after NACT compared with cases with no pCR. Interestingly, no differences were observed in terms of survival outcome between the micro-pR and macro-pR groups.11

Liang et al’s population showed a similar distribution of pR (pCR 11%, micro-pR 17%, and macr-o-pR 72%) and similar results in terms of progression-free survival (pCR vs micro-pR/macro-pR, undefined vs 11 months, P=0.02).21 In particular micro-pR and macro-pR disease showed the same progression-free survival (11 vs 11 months, P=0.54). No similar result was achieved for overall survival (pCR vs micro-pR/macro-pR, undefined vs 37 months, P=0.36). In the population analyzed there were no survival differences according to the residual disease after surgery (R0 vs R>0, progression-free survival 22 vs 10 months, P=0.10; overall survival undefined vs 35 months, P=0.27).21

As expected, the three categories of the CRS system were shown to correspond also with three different prognostic groups based on progression-free survival (CRS 1 and 2, 12 months vs CRS 3, 18 months; P<0.001) and overall survival (CRS 1 and 2, 28.4 months vs CRS 3, 45.1 months; P=0.15). Distribution of patients assigned to each of the three CRS groups was similar in the test and validation cohort (CRS 1, 0% and 7.0%; CRS 2, 70% and 66.2%; CRS 3, 30% and 26.8%; P=0.12).

Of note, complete resection was achieved in 54% of patients with CRS 1–2% and 78% of patients with CRS 3. Only a moderate but not significant trend toward longer progression-free survival was shown in patients with complete vs incomplete debulking. The authors conclude that pR, as an indicator of chemotherapy sensitivity, seems more important than debulking status for prognosis: favorable prognosis in completely debulked patients after NACT may be related to favorable tumor biology (CRS 3) rather than quality of surgical effort.22

Furthermore, the CA-125 response did not discriminate between CRS grades. Almost all patients showed more than 50% CA-125 reduction and more than two- thirds showed a more than 90% reduction distributed across CRS 1 to 3.

Unfortunately, no survival analysis including only patients with no residual disease after IDS was provided.

It is important to emphasize that the best prognostic group, CRS 3, includes also patients that have minimal residual tumor arranged in irregular clusters not exceeding 2 mm. These patients in fact have shown a clinical outcome similar to those with no residual tumor, thereby expanding the category of patients most sensitive to platinum-based chemotherapy from the previously reported 6%11 to about 30%.

Superimposable are the results published by Coghlan et al in the external cohort of 71 patients.27

In the cohort analyzed by Lee et al, the CRS system was successfully used to stratify patients with respect to prognosis: a significant trend toward a positive association between CRS and longer progression-free survival was in fact observed (P<0.001).26 However, significant differences came to light.

First of all, in this study, the authors found significant differences in longer progression-free survival between CRS 1 and CRS 2 (P<0.001) and CRS 2 and CRS 3 (P=0.046), respectively. In particular, the outcomes of patients whose tumors exhibiting CRS 2 (longer progression-free survival 15.7 months) were found to be similar to those of patients with CRS 3 (longer progression-free survival 18.6 months), unlike Böhm et al’s validation cohort.26 Moreover, the distribution of CRS in their cohort (CRS 1, 5.5%; CRS 2, 51.8%; CRS 3, 42.7%) was significantly different from that of Böhm et al's validation cohort. No gross residual disease after IDS was achieved in 23.8% of patients with CRS 1–2, and 48.9% of patients with CRS 3. However, there was no significant difference in the rate of optimal cytoreduction (residual tumor <1 cm) between the two groups (CRS 1–2, 81%; CRS 3, 83%). Residual disease after IDS was the most powerful prognostic factor in multivariate analysis, suggesting that no gross residual disease after IDS might overcome the partial response (CRS 2) after NACT.

It would be interesting, considering all possible selection bias, to know whether survival data of patients experiencing a CRS 3 are superimposable to the ones reported for women with EOC treated with optimal PDS.

Behind the PCR: the immune system

Böhm et al in 2016 analyzed 54 omental samples of FIGO stage IIIC and IV high-grade serous OC undergoing NATC-IDS.33 pR to chemotherapy was assessed in the IDS biopsies using the CRS. None of the IDS samples in this series scored as CRS1.

In the 25 available matched omental biopsies taken at pretreatment and at IDS, the authors observed marked levels of CD8 +T cells and CD45RO+memory cells both in CRS 2 and 3, essentially unchanged before NACT, and a significant reduction of the density of Foxp3 +cells in the stromal areas of the CRS3 'good' responder biopsies after NACT (P=0.02). In agreement with this data, after assessing the phenotype of the T cells, a decrease in the percentage of CD4 +T cells that were CD25 +Foxp3+in the CRS3 biopsies was observed (P=0.015). This finding was supported by a reduction in a Treg cell gene signature in post- vs pre-NACT samples that was more pronounced in good responders.

When studying the functional ability of the T cells in the biopsies to produce IFNγ as a marker of T-cell activation and antitumor response, post-NACT CRS3 patients had a significantly higher proportion of IFNγ+CD4+T cells (P=0.002).

However, the authors found that PD-L1 protein was significantly increased in post-NACT compared with pre-NACT biopsies irrespective of response to treatment (P=0.03) concluding that high expression of immune checkpoint molecules could impair the potential beneficial effects of chemotherapy in stimulating T-cell activation.

Moreover, the authors analyzed plasma major inflammatory cytokines (TNF, IL8, and IL6) finding significantly decreased levels after NACT (P=0.0008, P=0.001, and P=0.0006, respectively) irrespective of CRS score. Decreased levels of IL-10 were observed after NACT (P<0.001) while plasma IFNγ showed a trend toward an increase after treatment. IL17 plasma levels remained elevated after NACT (P=0.02).

Focusing on tumor-infiltrating lymphocytes (TIL), Lo et al analyzed matched pre- and post-NACT tumor samples from 26 serous OC patients.34 NACT was associated with increased densities of CD3+, CD8 +, CD8 +TIA-1+, PD-1 +, and CD20+TIL. They found three different response patterns (TILhigh, TILlow, and TILnegative) but no prognostic significance was shown.

Available evidence indicate that chemotherapy can enhance CD8/Th1/cytolytic TIL and may reduce Tregs but no information on the pR are usually provided.

How to predict a PCR: possible markers

CA125

Many papers have been published concerning the role of CA125 in predicting the outcome of advanced-stage EOC after NACT. However, the majority of them lack any information on the pR after NACT since it is not usually included in standard prognostic criteria such as residual disease after IDS, longer progression-free survival, and overall survival.

EOC patients with a percentage reduction of CA125 ≥90% (73% of 115) after NACT were more likely to have complete IDS (P=0.035), less likely to have a bowel resection (P<0.001), and more likely to have no viable tumor/microscopic disease with treatment effect (P<0.001).35

PET-CT

The PET-CT role for the assessment of treatment response in EOC has not been clarified yet.

A recent review calculated pooled sensitivity and specificity of PET/CT performance in various aspects of imaging of OC, however the paucity of data did not allow to draw conclusions on the PET-CT role after NACT.36

Martoni et al investigated the role of mid-cycle (after three courses of chemotherapy) PET/CT imaging as a prognostic factor for the assessment of early metabolic response in 42 advanced EOC patients undergoing NACT.37 Percentage changes in maximal standardized uptake value (∆-SUVmax) were compared with the pR. Of 17 patients presenting ∆-SUVmax=100%, 88% had a pCR or minimal residual disease at the end of NACT (six courses) while of 25 patients presenting ∆-SUVmax<100%, 76% had a viable residual disease at the end of NACT.37

Vallius et al examined the relationship between the decrease in omental SUVmax after NACT (three to four courses).38 The reduction in omental SUVmax was significantly corresponded with the extent of the histopathological evidence of treatment response (P=0.004): a cut-off value of 57% for the decrease in omental SUVmax was found to be able to differentiate histopathological responders from poor responders with a sensitivity of 89%, a specificity of 88%, and an AUC of 0.91.38

Interestingly, one study used PET/CT to assess treatment response toward temsirolimus, using metabolic parameters such as SUVmax and total lesion glycolysis to predict subsequent radiological response or disease progression in 20 patients with advanced breast, endometrial, and ovarian cancer (4, 5, and 11 patients respectively). Changes in total lesion glycolysis after 2 weeks predicted partial response after 10 weeks (P=0.037). A rise in SUV between the second and sixth week predicted progression (PD) (P=0.034) and was associated with worse longer progression free-survival (HR1.068; P=0.013).39 Given these encouraging data, it is probable that PET-CT assessment of treatment response will be further diffused with the development of novel targeted therapies.

Molecular subtypes and PR

In 2011, microarray-based gene expression profiling, performed by The Cancer Genome Atlas (TCGA) project, was used to classify high-grade serous OC into four gene expression subtypes: mesenchymal, immunoreactive, proliferative, or differentiated.40 These subtypes were reproducible in an Australian data set (C1, C2, C5, and C4, respectively).41 Both studies reported that tumors of mesenchymal phenotype (mesenchymal or C1) had poor prognoses, whereas immunoreactive or C2 tumors had favorable prognoses. Unfortunately, this classification showed limited clinical utility.

In 2015, Muramaki et al identified a histopathological classification of high-grade serous OC that significantly correlated with the TGCA gene expression subtypes.42 The authors’ analysis of 35 cases of EOC submitted to NACT using CLOVAR scores showed that the mesenchymal subtype is particularly sensitive to taxane. Unfortunately, no data on pR were provided.42

Gene signature

During the past 15 years, technological advances have led to the development of multiparametric genomic assays aimed at providing a new approach to the assessment of prognosis and response to treatments.43 44 However, a specific gene profile able to predict the achievement of a pCR after NACT in EOC patients has not been investigated yet.

MicroRNA

Despite the great amount of data describing the role of microRNA (miRNA) in the modulation of chemoresponsiveness/resistance to platinum-based agents in EOC patients, the association between miRNA and the pR has not been investigated directly.

Response to platinum agents is usually indirectly measured as relapse/progression rate. In Petrillo’s et al paper45 aimed at identifying miRNA families associated with response to platinum-based NACT and prognosis in EOC, data concerning pR are provided but no direct connection to miRNA is made.

PCR across various chemotherapy regimens

The standard schedule of NACT in unresectable EOC patients is based on carboplatin (AUC 5) plus paclitaxel (175 mg/m2), administrated every 3 weeks.4 As previously shown, the reported pCR rate (defined according to the CRS criteria) after this chemotherapy regimen varies from 4% to 30%.

In the past 10 years, however, a great effort has been made to test new chemotherapy regimens or to incorporate biological drugs in standard regimens potentially more effective than standard especially in the adjuvant setting. Whether the pCR rate changes according to chemotherapy regimen remains a major unanswered question.

The role of dose-dense paclitaxel-based chemotherapy such as NACT has been analyzed in just one retrospective series, and the authors reported a higher percentage of patients showing pCR in the dose-dense compared with the standard group (14% vs 3%; P=0.11).46 However, this data has not been confirmed in Ebata’s series, in which only 5.9% of patients undergoing neoadjuvant dose-dense weekly paclitaxel and carboplatin demonstrated pCR, a percentage that was similar to previous reports.20

The unique data available concerning the pR after a platinum and Bevacizumab-based NACT suggests a similar pCR rate compared with the one achieved in standard chemotherapy.47

Trials incorporating PARP-inhibitors in NACT for newly diagnosed EOC patients are currently ongoing awaiting preliminary data (NCT02470585 and NCT02477644).

Conclusions

pR to NACT emerges as an easily assessable and clinically useful prognostic tool in EOC patients. Increasing the rate of pCR to NACT, currently accounting for less than 10% of the overall population, appears as an attractive strategy to improve the lower progression-free survival reported in EOC patients receiving NACT. Therefore, it would be highly useful to include pathologic response as a future surrogate endpoint to be considered for drug development in this very challenging clinical setting. In this context, the incorporation into routine histological report of a simple, cost-free, reproducible scoring system could provide valuable prognostic information taking a potential step toward individualized treatments. Böhm‘s CRS seems suitable for this purpose, having been proven high reproducibility and prognostic significance in this setting of patients. From a biological point of view, studies on the immune microenvironment of post-NACT omental samples showed chemotherapy effects in stimulating T-cell activation, more markedly in CRS3 patients. However, this positive effect could be impaired by a high expression of immune checkpoint molecules such as PDL-1. This information provides a rationale for cancer immunotherapy, especially immune checkpoint blockade, at an early time point in these patients’ disease history. Currently, there are no available markers to predict a pCR. Not enough data have been published on CA125 serum levels. There is little evidence relating metabolic response in 18F-FDG PET/CT and pR to NACT but is it highly likely that this imaging modality will play an important role in the future. Unfortunately, neither the TGCA gene expression subtypes or Muramaki’s novel histopathological subtypes or miRNA signatures related to platinum response provide data on pR. The identification of a signature for CRS1 prediction (non-responders) would allow the personalization of up-front treatment, submitting these patients to PDS, even with bulky advanced disease.

In conclusion, with the increasing use of NACT in women with advanced EOC, pathologic response will progressively enter routine clinical practice as a useful marker, prospective clinical trials are required to establish and validate the best scoring system to be used, and to clarify the prognostic value of this measure.

References

  1. 1.
  2. 2.
  3. 3.
  4. 4.
  5. 5.
  6. 6.
  7. 7.
  8. 8.
  9. 9.
  10. 10.
  11. 11.
  12. 12.
  13. 13.
  14. 14.
  15. 15.
  16. 16.
  17. 17.
  18. 18.
  19. 19.
  20. 20.
  21. 21.
  22. 22.
  23. 23.
  24. 24.
  25. 25.
  26. 26.
  27. 27.
  28. 28.
  29. 29.
  30. 30.
  31. 31.
  32. 32.
  33. 33.
  34. 34.
  35. 35.
  36. 36.
  37. 37.
  38. 38.
  39. 39.
  40. 40.
  41. 41.
  42. 42.
  43. 43.
  44. 44.
  45. 45.
  46. 46.
  47. 47.

Footnotes

  • Contributors CN, AF, GFZ, EP, GS, and MP contributed to the design and implementation of the research, to the analysis of the results, and to the writing of the manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial, or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.