- Email: [email protected]
Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer
European Journal of Surgical Oncology xxx (xxxx) xxx
Contents lists available at ScienceDirect
European Journal of Surgical Oncology journal homepage: www.ejso.com
Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer Sumit Sahni a, b, c, Elizabeth A. Moon a, b, Viive M. Howell a, b, Shreya Mehta a, b, c, Nick Pavlakis a, b, d, e, David Chan a, b, d, e, Mahsa S. Ahadi a, b, f, Anthony J. Gill a, b, f, Jaswinder Samra a, b, c, g, Anubhav Mittal a, b, c, g, * a
Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Australia Kolling Institute of Medical Research, University of Sydney, Australia Australian Pancreatic Centre, St Leonards, Sydney, Australia d Northern Sydney Cancer Center, Royal North Shore Hospital, St Leonards, NSW, Australia e Northern Cancer Institute, St Leonards and Frenchs Forest, NSW, Australia f Cancer Diagnosis and Pathology Group, Kolling Institute of Medical Research, Royal North Shore Hospital, St Leonards, NSW, 2065, Australia g Upper GI Surgical Unit, Royal North Shore Hospital and North Shore Private Hospital, Australia b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 29 November 2019 Received in revised form 29 December 2019 Accepted 1 February 2020 Available online xxx
Background: Pancreatic ductal adenocarcinoma (PDAC) has been recently classified into four subtypes based on the gene expression levels, with squamous subtype having worst prognostic outcomes. However, gene expression analysis for each individual patient is not clinically feasible due to very high associated cost. We previously reported that levels of three biomarkers (S100A4, Ca-125 and Mesothelin) can be used to classify PDAC patients based on their survival outcomes. This project aimed to determine if this novel biomarker panel can be used as a surrogate to identify squamous PDAC subtype. Methods: Using the Nanostring gene expression platform, tumor tissue from 24 PDAC patients were analysed for our novel biomarkers and markers associated with four PDAC subtypes. Results: Gene expression of our biomarker panel (S100A4, Ca-125 and Mesothelin) closely clustered together with markers for squamous PDAC subtype. Conclusion: These results highlight the potential of our biomarkers to be utilized for identification of squamous PDAC subtype. © 2020 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.
Keywords: Pancreatic ductal adenocarcinoma Biomarkers Squamous subtype Gene expression analysis
Introduction Pancreatic ductal adenocarcinoma (PDAC) has one of the poorest long-term survival of all major cancers, with an average 6% (2e9%) 5-year survival post diagnosis [1]. Recent efforts in genomic analysis of tumor tissue from PDAC patients have led to classification of PDAC into four subtypes: squamous, pancreatic progenitor, aberrantly differentiated endocrine exocrine (ADEX) and immunogenic [2]. The squamous subtype is reported to have the worst prognosis and overall survival outcome of all four genetic subtypes
* Corresponding author. Upper Gastrointestinal Surgical Unit, Level 8A, Acute Services Building, Royal North Shore Hospital, Reserve Road, St. Leonards, NSW, 2065, Australia. E-mail address: [email protected] (A. Mittal).
[2]. The ability to accurately classify the PDAC subtype will allow for the delivery of individualized care for PDAC patients. However, genomic analysis of all patients for PDAC subtype classification is very expensive, and the cost has limited the integration of routine genomic sub-typing for PDAC patients. Despite published reports that not all PDAC has the same biology and response to treatment, the current staging and treatment of PDAC does not include biological measures of tumor aggressiveness, or the risk of occult metastatic disease. Multimodal treatment of PDAC with surgical resection and chemotherapy offers the only chance of cure. However, despite aggressive treatment, there is a high recurrence rate with metastatic disease within 12 months from surgery [3]. The high metastatic recurrence rate indicates that routine imaging for PDAC at the time of starting the treatment journey cannot identify patients with occult metastases and aggressive biology. For patients with predicted poor
https://doi.org/10.1016/j.ejso.2020.02.001 0748-7983/© 2020 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.
Please cite this article as: Sahni S et al., Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer, European Journal of Surgical Oncology, https://doi.org/10.1016/j.ejso.2020.02.001
2
S. Sahni et al. / European Journal of Surgical Oncology xxx (xxxx) xxx
survival and high risk of recurrent disease, such as the squamous genetic subtype, surgical resection brings uncertain survival benefit. Surgery may be associated with prolonged postoperative recovery periods of 3e6 months with a significant impact on patients’ quality of life without adding a significant survival benefit. Therefore, a cost-effective method based on tumor biology for personalised decision making in treating PDAC patients is urgently required. Recent reports have shown that tissue levels of a novel panel of three protein biomarkers (i.e., S100A4, Ca-125 and Mesothelin) using cost-effective immunohistochemistry (IHC) was able to stratify PDAC patients into four statistically different groups based on their overall survival [4]. The expression of all three biomarkers was shown to have worst overall survival, while patients with tumor expressing none of these proteins have the best overall survival outcome [4]. In this project, we aimed to assess if the mRNA expression levels of this novel biomarker panel (i.e., S100A4, Ca-125 and Mesothelin) could be used as a surrogate for identifying the genotype for squamous PDAC. Materials and methods Participants and tissue collection Patients who presented with histologically confirmed PDAC at a tertiary centre (Royal North Shore Hospital (RNSH) and North Shore Private Hospital (NSP), Sydney, Australia) between March 04, 2016 and October 24, 2017 were included in the study. Only patients for which formalin fixed paraffin embedded (FFPE) blocks of PDAC tissue were available were included in this study. Specimens with very low tumor cellularity (<20%; determined by experienced pathologist) were excluded from this study. This study was approved by the RNSH and NSP institutional ethics committees under references HREC/16/HAWKE/105 and NSPHEC 2016e007, respectively. Informed written consent was obtained from all participants and/or their designated surrogate. Northern Sydney Local Health District (NSLHD) reference: RESP/16/ 76. RNA extraction Hematoxylin and eosin (H&E) stained sections of tissue were marked for tumor regions by an experienced pathologist. In order to enrich samples with tumor tissue, FFPE sections (5 mm thickness) were macro-dissected based on the marked tumor regions. Total RNA was extracted using Qiagen RNeasy FFPE Kit (Cat# 73504; Qiagen, Hilden, Germany), following the manufacturer's protocol. RNA quality and quantification were determined by Agilent Bioanalyzer using Agilent RNA 6000 Nano Kit (Aligent Technologies, Santa Clara, CA). Gene expression analysis A customised Nanostring Elements Panel was utilized, which consisted of the tissue biomarker panel (S100A4, MUC16 and MSLN), and known markers for the four genetic subtypes of PDAC [2]: squamous (FSCN1, ADAM17, PGAM1, S100A2 and EGFR), progenitor (PDX1, MNX1 and FOXA2), ADEX (NR5A2, RBPJL and NEUROD1) and immunogenic (CD274 and CTL4A). Four housekeeping genes (ACTB, B2M, TBP and TUBB) were included in the panel for data normalization. RNA samples were processed according to manufacturer's established protocol [5]. Analysis of gene counts was performed using nSolver Analysis Software 4.0 (Nanostring Technologies). The heatmap agglomerative clustering analysis was performed on the normalized data (i.e.,
normalized to the housekeeping genes). Elucidean distance was utilized as a distance matrix, which calculates the distance between two samples (or genes) as the square root of the sum of squared differences in their log count values. Average linkage method was used, which calculates the distance between two clusters as the mean distance between their elements. Clustering was performed for both gene and sample data. Results Patient Characteristics A total of 24 pathologically confirmed PDAC patients (14 males, 10 females) with sufficient cellularity on the FFPE sections met the inclusion criteria for this study. Patient characteristics (age, sex, tumor stage) and survival data are described in Fig. 1. Novel biomarker panel is predictive of squamous PDAC subtype Heat map for gene expression levels was developed using agglomerative clustering. All squamous markers (i.e., FSCN1, ADAM17, PGAM1, S100A2 and EGFR) were observed to cluster closely together (Fig. 2). Interestingly, the tissue biomarker panel (S100A4, MUC16 and MSLN) also clustered together with markers for squamous subtype (Fig. 2). Markers for other PDAC subtypes also clustered together (CTLA4 and CD274 for immunogenic; MNX1 and PDX1 for progenitor; and NR5A2 and NEUROD1 for ADEX), with exception of FOXA2 (progenitor) and RBPJL (ADEX) which did not cluster together with other markers of their class. Discussion In this study, we have demonstrated that the gene expression levels of the IHC biomarker panel (S100A4, Ca-125 and Mesothelin) clusters together with the markers for squamous PDAC subtype which is known to have worst prognosis [2]. These findings provide an opportunity to develop a simple and cost-effective surrogate biomarker test for identifying squamous PDAC subtype. Significant advances have been made in identifying gene expression pattern of PDAC. In fact, a recent study has shown that PDAC patients can be divided into four subtypes based on their gene expression pattern [2]. Although this is critical step towards development of precision medicine approach in PDAC, gene expression analysis is not a cost-effective measure to implement in routine clinical practice. In fact, the cost of performing comprehensive genomic profiling using commercially available kits is several thousand dollars per patient [6] vs. IHC in a pathology lab which costs less than a hundred dollar per patient [7]. It has been previously reported that the three biomarker panel (S100A4, Ca-125 and Mesothelin) can be readily detected by IHC in pancreatic tumor tissue [4]. Notably, there was a significant (p < 0.001) difference in overall survival in patients who had triple positive biomarkers phenotype (median survival 12.8 months) compared to patients with triple negative biomarker phenotype (median survival 36.8 months) [4]. This current study demonstrate that this biomarker panel can also identify squamous PDAC subtype, which also has lowest survival outcomes [2]. In order to ensure wider availability and usage of diagnostic tests, World Health Organization (WHO) has established the ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free and Deliverable to end-users) guidelines, which acts as a benchmark especially under resource constrained settings [8]. Genomic analysis does not fit this criterion, due to high cost and requirement of specialized equipment. In contrast, IHC adheres to majority of benchmarks for ASSURED guidelines, being affordable,
Please cite this article as: Sahni S et al., Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer, European Journal of Surgical Oncology, https://doi.org/10.1016/j.ejso.2020.02.001
S. Sahni et al. / European Journal of Surgical Oncology xxx (xxxx) xxx
3
Fig. 1. Patient Characteristics. (A) Sex, number of patients, median age and disease stage of PDAC patients included in this study. (B) Kaplan Meier Survival curve for the patients included in this study.
Fig. 2. Heat Map Analysis. Novel Biomarker Panel (S100A4, MUC16 and MSLN) along with markers for squamous (FSCN1, ADAM17, PGAM1, S100A2 and EGFR), progenitor (PDX1, MNX1 and FOXA2), ADEX (NR5A2, RBPJL and NEUROD1) and immunogenic (CD274 and CTL4A). PDAC subtypes were subjected to agglomerative clustering to generate a heat map.
easy to use, highly sensitive, selective and robust technique, and require minimal specialized equipment support. Hence, development of an IHC based test for identification of squamous PDAC subtype will be highly beneficial, specially under resource constrained settings. Notably, a separate study with large, multi-institutional cohort has shown that levels of two biomarkers (i.e., S100A2 and S100A4), identified by IHC, also correlated with the squamous PDAC subtype [9]. This again re-emphasizes the potential for the use of surrogate biomarkers for the identification of genomic subtypes of PDAC using a simple and inexpensive technique (i.e., IHC). Importantly, IHC analyses can be readily performed on core biopsies obtained by endoscopic ultrasound (EUS) [10,11]. This provides an advantage in determining the squamous PDAC subtype using small amount of tumor core biopsy by EUS, rather than postresection samples. This would allow for personalisation of care for
PDAC patients. Major limitation of this study is a smaller patient cohort. However, despite the small numbers, the study was able to demonstrate a correlation between the tissue IHC biomarker positivity and the squamous subtype of PDAC. Another potential limitation is that, the tissue specimens utilized for RNA extraction were heterogenous mixture of tumor and stromal cells, which were macro-dissected for tumor enrichment. Future studies will improve on these limitations with a large cohort and micro-dissected tumor sections to further validate these results. Conclusion Despite the advances made in the management of pancreatic cancer, tumor biology still dictates long-term survival. A
Please cite this article as: Sahni S et al., Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer, European Journal of Surgical Oncology, https://doi.org/10.1016/j.ejso.2020.02.001
4
S. Sahni et al. / European Journal of Surgical Oncology xxx (xxxx) xxx
personalised and highly selective surgical approach to the management of PDAC patients results in better long-term survival. The use of an affordable and readily available test will allow for identification of patients who may not gain a survival advantage from surgery due to the nature of their tumor sub-type. Further multiinstitutional studies with a larger patient cohort will be required to further validate these results. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments A.M. would like to thank Sydney Vital for the Translational Centre for Excellence in Pancreatic Cancer Grant and R T Hall Trust for the RT Hall Trust grant. S.S. would like to thank Mr Guy Boncardo for the Boncardo Pancreatic Cancer Fellowship. S.S. would also like to thank AMP Foundation for the AMP Tomorrow Grant and Cancer Australia and Cure Cancer Australia for the Young Investigator PdCCRS grant. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.ejso.2020.02.001.
References [1] Ilic M, Ilic I. Epidemiology of pancreatic cancer. World J Gastroenterol 2016;22:9694e705. [2] Bailey P, Chang DK, Nones K, Johns AL, Patch AM, Gingras MC, et al. Genomic analyses identify molecular subtypes of pancreatic cancer. Nature 2016;531: 47e52. [3] Kim S, Itchins M, Arena J, Nahm C, Pavlakis N, Clarke S, et al. Patterns and determinants of recurrence for pancreatic ductal adenocarcinoma after resection. JOP J Pancreas (Online) 2017;18:458e64. [4] Nahm CB, Turchini J, Jamieson N, Moon E, Sioson L, Itchins M, et al. Biomarker panel predicts survival after resection in pancreatic ductal adenocarcinoma: a multi-institutional cohort study. Eur J Surg Oncol 2019;45:218e24. [5] Geiss GK, Bumgarner RE, Birditt B, Dahl T, Dowidar N, Dunaway DL, et al. Direct multiplexed measurement of gene expression with color-coded probe pairs. Nat Biotechnol 2008;26:317e25. [6] Elvin JA, Chura J, Gay LM, Markman M. Comprehensive genomic profiling (CGP) of ovarian clear cell carcinomas (OCCC) identifies clinically relevant genomic alterations (CRGA) and targeted therapy options. Gynecol Oncol Rep 2017;20:62e6. [7] Authority AAP, Net EEMS, Schedule MMB. External expert opinions for morphological pathology (histology and cytopathology). [8] Kosack CS, Page AL, Klatser PR. A guide to aid the selection of diagnostic tests. Bull World Health Organ 2017;95:639e45. [9] Dreyer SB, Pinese M, Jamieson NB, Scarlett CJ, Colvin EK, Pajic M, et al. Precision oncology in surgery: patient selection for operable pancreatic cancer. Ann Surg 2018. https://doi.org/10.1097/SLA.0000000000003143. [10] Yoshizawa N, Yamada R, Sakuno T, Inoue H, Miura H, Takeuchi T, et al. Comparison of endoscopic ultrasound-guided fine-needle aspiration and biopsy with 22-gauge and 25-gauge needles for the "precision medicine" of pancreatic cancer: a retrospective study. Medicine (Baltim) 2018;97:e11096. [11] Yamada R, Mizuno S, Uchida K, Yoneda M, Kanayama K, Inoue H, et al. Human equilibrative nucleoside transporter 1 expression in endoscopic ultrasonography-guided fine-needle aspiration biopsy samples is a strong predictor of clinical response and survival in the patients with pancreatic ductal adenocarcinoma undergoing gemcitabine-based chemoradiotherapy. Pancreas 2016;45:761e71.
Please cite this article as: Sahni S et al., Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer, European Journal of Surgical Oncology, https://doi.org/10.1016/j.ejso.2020.02.001
Contents lists available at ScienceDirect
European Journal of Surgical Oncology journal homepage: www.ejso.com
Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer Sumit Sahni a, b, c, Elizabeth A. Moon a, b, Viive M. Howell a, b, Shreya Mehta a, b, c, Nick Pavlakis a, b, d, e, David Chan a, b, d, e, Mahsa S. Ahadi a, b, f, Anthony J. Gill a, b, f, Jaswinder Samra a, b, c, g, Anubhav Mittal a, b, c, g, * a
Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Australia Kolling Institute of Medical Research, University of Sydney, Australia Australian Pancreatic Centre, St Leonards, Sydney, Australia d Northern Sydney Cancer Center, Royal North Shore Hospital, St Leonards, NSW, Australia e Northern Cancer Institute, St Leonards and Frenchs Forest, NSW, Australia f Cancer Diagnosis and Pathology Group, Kolling Institute of Medical Research, Royal North Shore Hospital, St Leonards, NSW, 2065, Australia g Upper GI Surgical Unit, Royal North Shore Hospital and North Shore Private Hospital, Australia b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 29 November 2019 Received in revised form 29 December 2019 Accepted 1 February 2020 Available online xxx
Background: Pancreatic ductal adenocarcinoma (PDAC) has been recently classified into four subtypes based on the gene expression levels, with squamous subtype having worst prognostic outcomes. However, gene expression analysis for each individual patient is not clinically feasible due to very high associated cost. We previously reported that levels of three biomarkers (S100A4, Ca-125 and Mesothelin) can be used to classify PDAC patients based on their survival outcomes. This project aimed to determine if this novel biomarker panel can be used as a surrogate to identify squamous PDAC subtype. Methods: Using the Nanostring gene expression platform, tumor tissue from 24 PDAC patients were analysed for our novel biomarkers and markers associated with four PDAC subtypes. Results: Gene expression of our biomarker panel (S100A4, Ca-125 and Mesothelin) closely clustered together with markers for squamous PDAC subtype. Conclusion: These results highlight the potential of our biomarkers to be utilized for identification of squamous PDAC subtype. © 2020 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.
Keywords: Pancreatic ductal adenocarcinoma Biomarkers Squamous subtype Gene expression analysis
Introduction Pancreatic ductal adenocarcinoma (PDAC) has one of the poorest long-term survival of all major cancers, with an average 6% (2e9%) 5-year survival post diagnosis [1]. Recent efforts in genomic analysis of tumor tissue from PDAC patients have led to classification of PDAC into four subtypes: squamous, pancreatic progenitor, aberrantly differentiated endocrine exocrine (ADEX) and immunogenic [2]. The squamous subtype is reported to have the worst prognosis and overall survival outcome of all four genetic subtypes
* Corresponding author. Upper Gastrointestinal Surgical Unit, Level 8A, Acute Services Building, Royal North Shore Hospital, Reserve Road, St. Leonards, NSW, 2065, Australia. E-mail address: [email protected] (A. Mittal).
[2]. The ability to accurately classify the PDAC subtype will allow for the delivery of individualized care for PDAC patients. However, genomic analysis of all patients for PDAC subtype classification is very expensive, and the cost has limited the integration of routine genomic sub-typing for PDAC patients. Despite published reports that not all PDAC has the same biology and response to treatment, the current staging and treatment of PDAC does not include biological measures of tumor aggressiveness, or the risk of occult metastatic disease. Multimodal treatment of PDAC with surgical resection and chemotherapy offers the only chance of cure. However, despite aggressive treatment, there is a high recurrence rate with metastatic disease within 12 months from surgery [3]. The high metastatic recurrence rate indicates that routine imaging for PDAC at the time of starting the treatment journey cannot identify patients with occult metastases and aggressive biology. For patients with predicted poor
https://doi.org/10.1016/j.ejso.2020.02.001 0748-7983/© 2020 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.
Please cite this article as: Sahni S et al., Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer, European Journal of Surgical Oncology, https://doi.org/10.1016/j.ejso.2020.02.001
2
S. Sahni et al. / European Journal of Surgical Oncology xxx (xxxx) xxx
survival and high risk of recurrent disease, such as the squamous genetic subtype, surgical resection brings uncertain survival benefit. Surgery may be associated with prolonged postoperative recovery periods of 3e6 months with a significant impact on patients’ quality of life without adding a significant survival benefit. Therefore, a cost-effective method based on tumor biology for personalised decision making in treating PDAC patients is urgently required. Recent reports have shown that tissue levels of a novel panel of three protein biomarkers (i.e., S100A4, Ca-125 and Mesothelin) using cost-effective immunohistochemistry (IHC) was able to stratify PDAC patients into four statistically different groups based on their overall survival [4]. The expression of all three biomarkers was shown to have worst overall survival, while patients with tumor expressing none of these proteins have the best overall survival outcome [4]. In this project, we aimed to assess if the mRNA expression levels of this novel biomarker panel (i.e., S100A4, Ca-125 and Mesothelin) could be used as a surrogate for identifying the genotype for squamous PDAC. Materials and methods Participants and tissue collection Patients who presented with histologically confirmed PDAC at a tertiary centre (Royal North Shore Hospital (RNSH) and North Shore Private Hospital (NSP), Sydney, Australia) between March 04, 2016 and October 24, 2017 were included in the study. Only patients for which formalin fixed paraffin embedded (FFPE) blocks of PDAC tissue were available were included in this study. Specimens with very low tumor cellularity (<20%; determined by experienced pathologist) were excluded from this study. This study was approved by the RNSH and NSP institutional ethics committees under references HREC/16/HAWKE/105 and NSPHEC 2016e007, respectively. Informed written consent was obtained from all participants and/or their designated surrogate. Northern Sydney Local Health District (NSLHD) reference: RESP/16/ 76. RNA extraction Hematoxylin and eosin (H&E) stained sections of tissue were marked for tumor regions by an experienced pathologist. In order to enrich samples with tumor tissue, FFPE sections (5 mm thickness) were macro-dissected based on the marked tumor regions. Total RNA was extracted using Qiagen RNeasy FFPE Kit (Cat# 73504; Qiagen, Hilden, Germany), following the manufacturer's protocol. RNA quality and quantification were determined by Agilent Bioanalyzer using Agilent RNA 6000 Nano Kit (Aligent Technologies, Santa Clara, CA). Gene expression analysis A customised Nanostring Elements Panel was utilized, which consisted of the tissue biomarker panel (S100A4, MUC16 and MSLN), and known markers for the four genetic subtypes of PDAC [2]: squamous (FSCN1, ADAM17, PGAM1, S100A2 and EGFR), progenitor (PDX1, MNX1 and FOXA2), ADEX (NR5A2, RBPJL and NEUROD1) and immunogenic (CD274 and CTL4A). Four housekeeping genes (ACTB, B2M, TBP and TUBB) were included in the panel for data normalization. RNA samples were processed according to manufacturer's established protocol [5]. Analysis of gene counts was performed using nSolver Analysis Software 4.0 (Nanostring Technologies). The heatmap agglomerative clustering analysis was performed on the normalized data (i.e.,
normalized to the housekeeping genes). Elucidean distance was utilized as a distance matrix, which calculates the distance between two samples (or genes) as the square root of the sum of squared differences in their log count values. Average linkage method was used, which calculates the distance between two clusters as the mean distance between their elements. Clustering was performed for both gene and sample data. Results Patient Characteristics A total of 24 pathologically confirmed PDAC patients (14 males, 10 females) with sufficient cellularity on the FFPE sections met the inclusion criteria for this study. Patient characteristics (age, sex, tumor stage) and survival data are described in Fig. 1. Novel biomarker panel is predictive of squamous PDAC subtype Heat map for gene expression levels was developed using agglomerative clustering. All squamous markers (i.e., FSCN1, ADAM17, PGAM1, S100A2 and EGFR) were observed to cluster closely together (Fig. 2). Interestingly, the tissue biomarker panel (S100A4, MUC16 and MSLN) also clustered together with markers for squamous subtype (Fig. 2). Markers for other PDAC subtypes also clustered together (CTLA4 and CD274 for immunogenic; MNX1 and PDX1 for progenitor; and NR5A2 and NEUROD1 for ADEX), with exception of FOXA2 (progenitor) and RBPJL (ADEX) which did not cluster together with other markers of their class. Discussion In this study, we have demonstrated that the gene expression levels of the IHC biomarker panel (S100A4, Ca-125 and Mesothelin) clusters together with the markers for squamous PDAC subtype which is known to have worst prognosis [2]. These findings provide an opportunity to develop a simple and cost-effective surrogate biomarker test for identifying squamous PDAC subtype. Significant advances have been made in identifying gene expression pattern of PDAC. In fact, a recent study has shown that PDAC patients can be divided into four subtypes based on their gene expression pattern [2]. Although this is critical step towards development of precision medicine approach in PDAC, gene expression analysis is not a cost-effective measure to implement in routine clinical practice. In fact, the cost of performing comprehensive genomic profiling using commercially available kits is several thousand dollars per patient [6] vs. IHC in a pathology lab which costs less than a hundred dollar per patient [7]. It has been previously reported that the three biomarker panel (S100A4, Ca-125 and Mesothelin) can be readily detected by IHC in pancreatic tumor tissue [4]. Notably, there was a significant (p < 0.001) difference in overall survival in patients who had triple positive biomarkers phenotype (median survival 12.8 months) compared to patients with triple negative biomarker phenotype (median survival 36.8 months) [4]. This current study demonstrate that this biomarker panel can also identify squamous PDAC subtype, which also has lowest survival outcomes [2]. In order to ensure wider availability and usage of diagnostic tests, World Health Organization (WHO) has established the ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free and Deliverable to end-users) guidelines, which acts as a benchmark especially under resource constrained settings [8]. Genomic analysis does not fit this criterion, due to high cost and requirement of specialized equipment. In contrast, IHC adheres to majority of benchmarks for ASSURED guidelines, being affordable,
Please cite this article as: Sahni S et al., Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer, European Journal of Surgical Oncology, https://doi.org/10.1016/j.ejso.2020.02.001
S. Sahni et al. / European Journal of Surgical Oncology xxx (xxxx) xxx
3
Fig. 1. Patient Characteristics. (A) Sex, number of patients, median age and disease stage of PDAC patients included in this study. (B) Kaplan Meier Survival curve for the patients included in this study.
Fig. 2. Heat Map Analysis. Novel Biomarker Panel (S100A4, MUC16 and MSLN) along with markers for squamous (FSCN1, ADAM17, PGAM1, S100A2 and EGFR), progenitor (PDX1, MNX1 and FOXA2), ADEX (NR5A2, RBPJL and NEUROD1) and immunogenic (CD274 and CTL4A). PDAC subtypes were subjected to agglomerative clustering to generate a heat map.
easy to use, highly sensitive, selective and robust technique, and require minimal specialized equipment support. Hence, development of an IHC based test for identification of squamous PDAC subtype will be highly beneficial, specially under resource constrained settings. Notably, a separate study with large, multi-institutional cohort has shown that levels of two biomarkers (i.e., S100A2 and S100A4), identified by IHC, also correlated with the squamous PDAC subtype [9]. This again re-emphasizes the potential for the use of surrogate biomarkers for the identification of genomic subtypes of PDAC using a simple and inexpensive technique (i.e., IHC). Importantly, IHC analyses can be readily performed on core biopsies obtained by endoscopic ultrasound (EUS) [10,11]. This provides an advantage in determining the squamous PDAC subtype using small amount of tumor core biopsy by EUS, rather than postresection samples. This would allow for personalisation of care for
PDAC patients. Major limitation of this study is a smaller patient cohort. However, despite the small numbers, the study was able to demonstrate a correlation between the tissue IHC biomarker positivity and the squamous subtype of PDAC. Another potential limitation is that, the tissue specimens utilized for RNA extraction were heterogenous mixture of tumor and stromal cells, which were macro-dissected for tumor enrichment. Future studies will improve on these limitations with a large cohort and micro-dissected tumor sections to further validate these results. Conclusion Despite the advances made in the management of pancreatic cancer, tumor biology still dictates long-term survival. A
Please cite this article as: Sahni S et al., Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer, European Journal of Surgical Oncology, https://doi.org/10.1016/j.ejso.2020.02.001
4
S. Sahni et al. / European Journal of Surgical Oncology xxx (xxxx) xxx
personalised and highly selective surgical approach to the management of PDAC patients results in better long-term survival. The use of an affordable and readily available test will allow for identification of patients who may not gain a survival advantage from surgery due to the nature of their tumor sub-type. Further multiinstitutional studies with a larger patient cohort will be required to further validate these results. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments A.M. would like to thank Sydney Vital for the Translational Centre for Excellence in Pancreatic Cancer Grant and R T Hall Trust for the RT Hall Trust grant. S.S. would like to thank Mr Guy Boncardo for the Boncardo Pancreatic Cancer Fellowship. S.S. would also like to thank AMP Foundation for the AMP Tomorrow Grant and Cancer Australia and Cure Cancer Australia for the Young Investigator PdCCRS grant. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.ejso.2020.02.001.
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Please cite this article as: Sahni S et al., Tissue biomarker panel as a surrogate marker for squamous subtype of pancreatic cancer, European Journal of Surgical Oncology, https://doi.org/10.1016/j.ejso.2020.02.001