Journal of Clinical and Diagnostic Research, ISSN - 0973 - 709X

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Aug 2018

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Thanking you
With sincere regards
Dr. Rajendra Kumar Ghritlaharey, M.S., M. Ch., FAIS
Associate Professor,
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Kamla Nehru & Hamidia Hospitals Bhopal, Madhya Pradesh 462 001 (India)
On May 11,2011

Dr. Shankar P.R.

"On looking back through my Gmail archives after being requested by the journal to write a short editorial about my experiences of publishing with the Journal of Clinical and Diagnostic Research (JCDR), I came across an e-mail from Dr. Hemant Jain, Editor, in March 2007, which introduced the new electronic journal. The main features of the journal which were outlined in the e-mail were extensive author support, cash rewards, the peer review process, and other salient features of the journal.
Over a span of over four years, we (I and my colleagues) have published around 25 articles in the journal. In this editorial, I plan to briefly discuss my experiences of publishing with JCDR and the strengths of the journal and to finally address the areas for improvement.
My experiences of publishing with JCDR: Overall, my experiences of publishing withJCDR have been positive. The best point about the journal is that it responds to queries from the author. This may seem to be simple and not too much to ask for, but unfortunately, many journals in the subcontinent and from many developing countries do not respond or they respond with a long delay to the queries from the authors 1. The reasons could be many, including lack of optimal secretarial and other support. Another problem with many journals is the slowness of the review process. Editorial processing and peer review can take anywhere between a year to two years with some journals. Also, some journals do not keep the contributors informed about the progress of the review process. Due to the long review process, the articles can lose their relevance and topicality. A major benefit with JCDR is the timeliness and promptness of its response. In Dr Jain's e-mail which was sent to me in 2007, before the introduction of the Pre-publishing system, he had stated that he had received my submission and that he would get back to me within seven days and he did!
Most of the manuscripts are published within 3 to 4 months of their submission if they are found to be suitable after the review process. JCDR is published bimonthly and the accepted articles were usually published in the next issue. Recently, due to the increased volume of the submissions, the review process has become slower and it ?? Section can take from 4 to 6 months for the articles to be reviewed. The journal has an extensive author support system and it has recently introduced a paid expedited review process. The journal also mentions the average time for processing the manuscript under different submission systems - regular submission and expedited review.
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Overall, the publishing process with JCDR has been smooth, quick and relatively hassle free and I can recommend other authors to consider the journal as an outlet for their work."

Dr. P. Ravi Shankar
KIST Medical College, P.O. Box 14142, Kathmandu, Nepal.
On April 2011

Dear team JCDR, I would like to thank you for the very professional and polite service provided by everyone at JCDR. While i have been in the field of writing and editing for sometime, this has been my first attempt in publishing a scientific paper.Thank you for hand-holding me through the process.

Dr. Anuradha
On Jan 2020

Important Notice

Original article / research
Year : 2022 | Month : December | Volume : 16 | Issue : 12 | Page : EC05 - EC09 Full Version

Angiogenic Index as a Measure of Angiogenesis in Prostate Cancer and Its Correlation with Gleason Grade and Score

Published: December 1, 2022 | DOI:
Shikha Prakash, Prashant Singh, Pooja Nagayach, Kalpana Singh, Rajni Bharti, Gunjan Prakash

1. Assistant Professor, Department of Pathology, Sarojini Naidu Medical College, Agra, Uttar Pradesh, India. 2. Assistant Professor, Department of Pathology, Sarojini Naidu Medical College, Agra, Uttar Pradesh, India. 3. Assistant Professor, Department of Pathology, Sarojini Naidu Medical College, Agra, Uttar Pradesh, India. 4. Professor, Department of Pathology, Sarojini Naidu Medical College, Agra, Uttar Pradesh, India. 5. Professor, Department of Pathology, Sarojini Naidu Medical College, Agra, Uttar Pradesh, India. 6. Associate Professor, Department of Ophthalmology, FH Medical College, Firozabad, Uttar Pradesh, India.

Correspondence Address :
Dr. Gunjan Prakash,
B-2/22, Kamla Nagar, Agra-282005, Uttar Pradesh, India.


Introduction: Microvessel density, as a measure of angiogenesis, predicts prognosis in prostate cancer. Angiogenic Index (AI, numerical value of angiogenesis) minimises the possible variation concerning the width of the microscopic field, stromal epithelial relations and cellular tumour size.

Aim: To study AI in prostate cancer and its correlation with Gleason Grade (GG) and Gleason Score (GS).

Materials and Methods: The present cross-sectional, study was done at Postgraduate Department of Pathology, Sarojini Naidu Medical College, Agra, India, from September 2019 to December 2020. Twenty five histopathologically confirmed prostate adenocarcinoma specimens from radical prostatectomy, Transurethral Resection of Prostate (TURP), and needle biopsy were included in the study. These cases were categorised according to Gleason Grade (GG); Gleason Score (GS) was assigned to each case. The GSs were simplified into three groups: low (GS 2-6), intermediate (GS 7) and high-grade (GS 8-10). Immunohistochemical {Cluster Differentiation (CD) 31} blood vessel staining was done to calculate AI. Statistical significance was determined by Unpaired t-test.

Results: All the cases were males with age range from 55-76 years (mean age was 65.48±5.62 years). Mean AI was 13.74, 83.76, 163.27, 299.12 for the GG1, GG3, GG4, GG5, respectively. Mean AI was 29.72, 82.67, 129.15, 190.31, 206.71, 307.34 for GS 2, 6, 7, 8, 9, 10, respectively. Comparing GG among themselves, statistically significant difference in AI was found between GG3 vs GG4 (p-value=0.0056, r-value=0.5269). Difference was also statistically significant between GG3 vs GG5 (p-value=0.000011, r-value=0.8030) and GG4 vs GG5 (p-value=0.0036, r-value=0.5806). In all scores combined, the mean AI was 56.20 for low-grade (GS 2-6), 129.15 for intermediate-grade (GS 7), 247.35 for high-grade (GS 8-10). Statistically significant difference was found in between AI (p-value <0.05) in all Gleason scores.

Conclusion: Positive correlation was observed between AI, GG and GS in prostatic adenocarcinoma. AI may be of immense value to predict prognosis of prostatic adenocarcinoma.


Microvessel density, Prognosis, Prostatectomy, Prostate adenocarcinoma

Worldwide, clinically detected prostate cancer is the second most common malignancy, with an estimated 1.41 million new cases in 2020 (1). Incidence is low in Asian and North African countries but on the rise in India (2),(3). Most cases of prostate carcinoma are diagnosed after the age of 50 years, and frequency increases with age (4).

Angiogenesis is implicated as part of the process of tumour metastasis. Since the clinical significance of Microvessel Density (MVD) in human prostate cancer tissues was first reported by Weidner N et al., (5), several reports have shown that MVD is increased in carcinogenesis [6-10]. MVD is significantly associated with pathological features and outcomes in patients with prostate cancer (11). Antiangiogenic therapy might be a novel treatment option in advanced or metastatic prostatic carcinoma (12).

Earlier methods to quantify the microvessels in a tumour were microvessel count, MVD and maximal MVD. A different method of quantification of vascularisation is the Angiogenic Index (AI) that has been found to be associated with greater tumour size and grade, lymph node metastases and early death in cancer of breast (13).

Laforga JB and Aranda FI determined the number of microvessels by 1,000 tumour cells (AI) to perform a more accurate method for counting microvessels in breast cancer cases (13). This method minimised the possible variations concerning the width of the microscopic fields, stroma/epithelium relations and cellular tumour size. Results showed that the AI correlated more significantly than the classic MVD determination with other prognostic factors in breast cancer. Therefore, they recommended determining AI because of its reliable calculation and significant correlation with other prognostic factors (13).

Assessing angiogenesis with a numerical value that can be evaluated in small biopsy specimen will have more reproducibility than just counting MVD. No study is reported regarding AI measurement in prostate cancer. As blood microvessels are essential for tumour growth, the present study was performed to calculate the angiogenic index (using CD31 marker) in prostate cancer.

Cluster Differentiation 31 is more specific for endothelial cells than CD34 (14) and has been described on human blood platelets, monocytes, neutrophils, as well as on large and small vessels’ endothelial cells and naïve T-lymphocytes. Silberman MA et al., also used CD31 for staining microvessels (15). Hence, the present study was aimed to evaluate the angiogenic index in prostate cancer and its correlation with Gleason Grade (GG) and Gleason Score (GS) using Gleason System (histological prognostic factor).

Material and Methods

This cross-sectional study was conducted in Postgraduate Department of Pathology, Sarojini Naidu Medical College, Agra, India, from September 2019 to December 2020. Ethical clearance was obtained from Institutional Ethics Committee (SNMC/IEC/2022/130). Written consent was taken from the patients and their confidentiality was maintained.

Inclusion criteria: All the prostatectomy, Transurethral Resection of Prostate (TURP), needle biopsy specimens with definite histopathological diagnosis of prostate cancer were included in the study.

Exclusion criteria: Very small needle biopsy specimens (≤1 mm) and samples with extensive necrosis were excluded from the study.

Sample size calculation: Total 25 cases were included, of which 14 cases were fresh (during the study period) and 11 cases were archival (December 2018 to August 2019) formalin-fixed and paraffin-embedded diagnosed adenocarcinoma samples of needle biopsy (four cases), TURP (12 cases) and radical prostatectomy (nine cases).

Study Procedure

On Haematoxylin and Eosin (H&E) sections, the cases of prostate adenocarcinoma were categorised according to Gleason Grading (GG) system (16). It is based on the degree of glandular differentiation and growth pattern of the tumour in relation to the stroma as evaluated on low power (4X, 10X objective eye piece) examination. The predominant (primary) tumour pattern was graded according to Gleason pattern from GG1 to GG5; non dominant (secondary) tumour pattern was similarly graded according to Gleason Pattern (16). Gleason Score is obtained by adding these two values together.

Further, the scores were simplified in three groups as described by Humphrey PA (17):

a) Low-grade (GS2-6)
b) Intermediate-grade (GS7)
c) High-grade (GS8-10)

Immunohistochemical staining for Cluster Differentiation (CD) 31 was performed by means of a modified labelled avidin-biotin technique in which a biotinylated secondary antibody forms a complex with peroxidase-conjugated streptavidin molecules using monoclonal antibody and staining kit (Universal DAKO Labelled Streptavidin-Biotin®2 System, Horseradish Peroxidase, Denmark; DAKO LSAB®2 System, HRP) (14).

Calculation of Angiogenic Index

Counting procedure: Counting of vessels was done in three consecutive high-power fields (x400, Olympus CH20i). The total number of microvessels was recorded along with the number of nuclei of tumour cells located across the central straight line drawn across the maximum diameter of the eyepiece. The cell count was calculated as equal to π(n/2)2, where ‘π’ is equal to 3.14 and ‘n’ is the number of nuclei that intercept the line (13). Angiogenic index was calculated for each field and mean was derived.

In cases with primary and secondary Gleason grades, AI was calculated in individual grades in the similar way and the mean of the two grade was considered for those cases. To avoid bias, counting was done by two different observers and average AI was noted.

Statistical Analysis

Data was entered in Microsoft excel software and analysis was done using Statistical Package for the Social Science (SPSS) software version SPSS-12. The data was analysed to determine statistical significance using unpaired t-test and p-value ≤0.05 was considered significant.


All the 25 specimens were males and the age of cases ranged from 55-76 years with a mean age of 65.48±5.62 years. Fourteen showed single GG and 11 showed variable (primary grade+secondary grade) GG making a total of 36 variables to be studied (Table/Fig 1). GG1 adenocarcinoma was identified in one (2.78%) of 36 variables studied. GG3 (Table/Fig 2) was identified in 12 (33.33%) of 36 variables, GG4 was identified in 14 (38.89%) of 36 variables and GG5 (Table/Fig 3) was detected in nine of 36 (25%) variables studied. On Gleason Scoring, there was overlapping between various grades (Table/Fig 4). Seven study cases were of Intermediate Grade (Table/Fig 5) and 12 were High-Grade.

In Gleason grade 1 adenocarcinoma, the angiogenic index ranged from 15.64-40.28. Mean AI was 29.72. The range and mean values of angiogenic index for other Gleason grades (Table/Fig 6) are tabulated.

On comparing the mean AI in GG3 (83.76) and GG4 (163.27) adenocarcinoma, statistically significant difference (p-value=0.0056) was found (Table/Fig 7). On comparing the mean AI in GG3 (83.76) and GG5 (299.12) adenocarcinoma, a statistically significant difference (p-value=0.000011) was observed. On comparing the mean AI in GG4 (163.27) and GG5 (299.12) adenocarcinoma, the difference was statistically significant (p-value=0.0036). Only single case of GG1 was there, so no correlation could be carried out for this grade.

The range and mean values of AI for different Gleason scores (Table/Fig 8) are tabulated. Statistically significant difference (p-value <0.05) was found amongst all Gleason scores (Table/Fig 9). Mean AI increased from low-grade to intermediate-grade to high-grade. There was statistically significant difference in AI in cases with intermediate-grade and high-grade prostatic adenocarcinoma (p-value <0.02) (Table/Fig 10).

No statistically significant difference (p-value >0.05) was seen on comparing the AI between GG (mean AI=143.97) and GS (mean AI=157.65).


Angiogenic index has been found to be a reliable quantitative measure of angiogenesis in immunohistochemistry-stained sections (13). In this study, IHC marker CD31 was used to highlight blood vessels. The degree of tumour angiogenesis was determined by measuring AI. An increase in microvessel count was observed from low-grade to high-grade cancers.

Silberman MA et al., examined the relationship of MVD in intermediate grade prostate carcinomas with stage at radical prostatectomy (RP) and progression after RP (15). They observed MVD (using CD31) and Gleason score were independent statistically significant predictors of progression. Similar findings were reported by Strohmeyer D et al., (7). Brawer MK et al., demonstrated that MVD in prostatic carcinoma is an independent predictor of pathologic stage and, presumably, malignant potential (18). Contrarily, Arakawa A et al., observed that Gleason Score, but not MVC, was the best prognostic indicator in their study (19). CD-31 can detect pre-existing and newly formed vessels in cancer tissues (20). Parums DV et al., reported CD31 (antibody JC70) to be more specific, more sensitive and more reproducible in staining blood microvessels. JC70 does not stain lymphatic endothelium in benign lesions (21).

Comparing AI of intermediate grade (score 7) with high-grade (score 8-10), we found that the difference in Angiogenic index was statistically significant (p-value <0.02) (Table/Fig 9). The increase in microvessels from low to high grade, as observed in various studies, is tabulated (Table/Fig 11) (8),(9),(10),(15),(18),(19),(22),(23),(24). The present study results were in accordance with the findings of Upadhyay P et al., Gautam KA et al., Bigler A et al., (9),(10),(22). Strohmeyer D et al., revealed that tumour angiogenesis was associated with a negative clinical prognosis in prostate cancer after radical prostatectomy (23). Bostwick DG et al., showed a statistically significant contribution of MVD (along with Gleason score) in the prediction of pathologic stage (8). In the present study, the cases were divided according to different Gleason grades of adenocarcinoma. On comparison of GG among themselves, statistically significant difference in AI was found between GG3 vs GG4 (p-value=0.003). The difference was also statistically significant between GG3 vs GG5 (p-value=0.0003), GG4 vs GG5 (p-value=0.007). Also, statistically significant difference was found in between AI (p-value <0.05) in all Gleason scores. The observations of this study were in agreement with Upadhyay P et al., and Bettencourt MC et al., (9),(24). They found that the MVD in the tumour area significantly increased with increasing Gleason score and nuclear grade. In the present study, comparing the angiogenic index between grade (mean AI: 143.97) and score (mean AI: 157.65), no statistically significant difference (p-value >0.05) was found.

Gleason grading system is simplified (in low sample size studies) by compressing the scores into three groups: low-grade (score 2-6), intermediate-grade (score 7), high-grade (score 8-10) (17). In the present study, AI was calculated in various Gleason scores. No studies have been reported to find out AI in prostate cancer so a comparison cannot be done. Other authors have reported MVC values, but there was variation in the values as different methods were used (Table/Fig 12) (10),(25). Microvessel density has not always been an independent prognostic parameter for prostate cancer (26). Such disparate findings may be due to the use of different antibodies and immunohistochemistry techniques, tumour heterogeneity or the practice of analysing the most vascular portion of the tumour, which introduces a subjective assessment into the analysis. It was also noted, in almost all the sections there was an increased background staining owing to the cytoplasmic staining of tumour cells. This might be due to the presence of angiogenic factors in the cytoplasm of tumour cells.


The limitation of the present study was smaller sample size. Also, only a single IHC marker was used due to cost constraints. Follow-up of patients would have been useful to correlate angiogenic index with prognosis.


Angiogenic index seems to be more reliable method in quantifying angiogenesis as it minimises the possible variations concerning the width of the microscopic fields, stroma/epithelium relations and cellular tumour size. It can be used especially in TURP and needle biopsy specimens where grading and scoring may not be proper due to small tissue size. Future large-scale studies similar studies should be done to come to a consensus for the prognostic cut-off value of the Angiogenic Index. Further studies should also include the correlation of AI with the clinical outcome of the patients, so that the prediction of the prognosis may be supported by the AI values in prostatic adenocarcinoma cases. The subsequent compilation of similar multi-centric studies may result in the overall better management of prostatic adenocarcinoma patients.


The authors wish to thank all laboratory technicians who were closely associated in the study and contributed in one or the other way.


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DOI and Others

DOI: 10.7860/JCDR/2022/59041.17234

Date of Submission: Jul 12, 2022
Date of Peer Review: Sep 03, 2022
Date of Acceptance: Oct 26, 2022
Date of Publishing: Dec 01, 2022

• Financial or Other Competing Interests: None
• Was Ethics Committee Approval obtained for this study? Yes
• Was informed consent obtained from the subjects involved in the study? Yes
• For any images presented appropriate consent has been obtained from the subjects. Yes

• Plagiarism X-checker: Aug 16, 2022
• Manual Googling: Oct 07, 2022
• iThenticate Software: Oct 21, 2022 (13%)

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