Roche uPath IVD User manual

uPath PD-L1 (SP263) image analysis for

Non-Small Cell Lung Cancer

Algorithm Guide

Table of Contents

Introduction 1

Algorithm Summary and Explanation 2

Intended Use 3

Intended Use of product 3

Purpose of Algorithm Guide 3

Clinical Signiﬁcance 4

Test Principles 5

Limitations 6

Data Security 7

Workﬂow for using the uPath PD-L1 image analysis for NSCLC Algorithm 8

Pathologist Workﬂow 9

PD-L1 Image Analysis 12

PD-L1 Evaluation 15

PD-L1 Algorithm Stain Evaluation 15

Staining Characteristics 15

Performance Characteristics 26

Method Comparison 26

Pathologist Reproducibility Studies 27

Scanner Reproducibility Studies 28

Troubleshooting 29

References 33

Introduction

The Roche uPath enterprise software (uPath enterprise software)

with the uPath PD-L1 (SP263) image analysis for Non-Small Cell

Lung Cancer (NSCLC) algorithm (uPath PD-L1 (SP263) image

analysis for NSCLC algorithm) is a software system designed to

assist in the quantitative assessment of protein expression in

immunohistochemically (IHC) stained histologic sections from

formalin-ﬁxed, parafﬁn-embedded (FFPE) normal and neoplastic

tissues.

The uPath enterprise software is an end-to-end digital pathology

software solution that allows pathology laboratories to acquire,

manage, view, analyze, share, and report on digital images of

pathology specimens. Using the uPath enterprise software, the

pathologist can view digital images at various magniﬁcations,

add annotations, make tissue section measurements, perform

image analysis, and generate reports.

Note: The uPath PD-L1 (SP263) image analysis for NSCLC

algorithm is an adjunctive computer-assisted methodology to aid

in the acquisition and measurement of images from microscope

glass slides of tissue specimens IHC-stained for the presence

of PD-L1 protein. To assure the validity of image analysis scores,

it is the responsibility of the pathologist to verify agreement by

employing appropriate controls as speciﬁed in the VENTANA

PD-L1 (SP263) Rabbit Monoclonal Primary Antibody method

sheet (available at www.ventana.com).

uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide 1

2 uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide

Algorithm Summary and Explanation

For the image analysis applications, the pathologist may use the

uPath enterprise software to select and outline one or several

regions of interest (ROIs), and each ROI may be viewed at various

magniﬁcations and then analyzed by the uPath PD-L1 (SP263)

image analysis for NSCLC algorithm. A count of the total number

of target TC is generated and tumor cells (TC) are stratiﬁed by

whether they are stained or unstained. The uPath PD-L1 (SP263)

image analysis for NSCLC algorithm divides the stained TC by

the total number of TC (stained and unstained) to generate the

PD-L1 TC Positivity score on a scale of 0-100%. The uPath PD-L1

(SP263) image analysis for NSCLC algorithm can generate a

score for a particular ROI, or an aggregate score for all selected

ROIs on that slide. Though the algorithm detects non-tumor

cells as part of the overall analysis, the overlay and output only

shows the TC used in the calculation of TC Positivity score. The

pathologist can accept the score provided by the uPath PD-L1

(SP263) image analysis for NSCLC algorithm, or may override

the score with a different score. The pathologist must carefully

review to what the algorithm has marked as positive and negative

TC and conﬁrm the algorithm is correct or provide a manual

override. The uPath PD-L1 (SP263) image analysis for NSCLC

algorithm does not make independent interpretations of the

data and therefore should only be used by a qualiﬁed pathologist

in conjunction with histological examination, relevant clinical

information, and proper controls. It is designed and indicated as

an aid to the pathologist for the assessment of PD-L1 expression

at the 50%.

Intended Use

Purpose of Algorithm Guide

This uPath PD-L1 (SP263) image analysis for NSCLC Algorithm

Guide (Algorithm Guide) is intended to:

• Provide background information on the intended use of the

uPath PD-L1 (SP263) image analysis for NSCLC algorithm, test

principles and limitations.

• Deﬁne the necessary materials, IT, data security and network

requirements.

• Show step-wise directions for running the uPath PD-L1 (SP263)

image analysis for NSCLC algorithm.

• Provide photographic images that illustrate how the uPath

PD-L1 (SP263) image analysis for NSCLC algorithm should be

used.

• Provide pathologists with a tool to facilitate the use of the uPath

PD-L1 (SP263) image analysis for NSCLC algorithm on FFPE

NSCLC sections stained with the VENTANA PD-L1 (SP263)

Assay.

• Provide example images of challenging cases to provide

guidance on how to use the uPath PD-L1 (SP263) image

analysis for NSCLC algorithm in their evaluation.

• Show performance characteristics of the uPath PD-L1 (SP263)

image analysis for NSCLC algorithm.

Intended Use of product

The uPath PD-L1 (SP263) Image Analysis for NSCLC algorithm is

intended for use as an aid to the pathologist in the detection and

semi-quantitative measurement of PD-L1 protein in formalin-

ﬁxed, parafﬁn-embedded NSCLC tissue. When used with the

VENTANA PD-L1 (SP263) Assay, it is indicated for use as an aid

in identifying patients with NSCLC for treatment with therapies

with the ≥ 50% PD-L1 TC positivity cutoff in accordance with the

approved therapeutic product labeling.

Note: The uPath PD-L1 (SP263) Image Analysis for NSCLC is

an adjunctive computer-assisted methodology to aid in the

acquisition and measurement of images from microscope glass

slides of tissue specimens IHC-stained for the presence of

PD-L1 protein. To assure the validity of image analysis scores, it

is the responsibility of the pathologist to verify agreement and

employ appropriate controls as speciﬁed in the VENTANA PD-L1

(SP263) Assay method sheet (P/N 741-4905).

This algorithm is intended for in vitro diagnostic (IVD) use.

uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide 3

Clinical Signiﬁcance

Lung cancer has been the most common cancer in the world for

several decades and remains the leading cause of cancer deaths

worldwide. It is estimated to account for 12.9% of all new cancer

cases and is responsible for nearly 1.76 million deaths annually

worldwide, or approximately one in ﬁve cancer-related deaths.

NSCLC, is the most common type of lung cancer accounting

for approximately 85% of all lung cancer cases. The majority of

patients with NSCLC present with inoperable, locally advanced

disease (Stage IIIB) or metastatic disease (Stage IV), neither of

which currently has any curative treatment options. The 5-year

relative survival rate for NSCLC diagnosed in advanced stages is

4.7%.

The programmed death-ligand 1 (PD-L1) is a transmembrane

protein expressed on activated T cells that downregulates the

immune response by binding to its two inhibitory receptors

programmed death-1 (PD-1) and B7-1 (CD80). Binding of PD-

L1 with PD-1 inhibits T cell proliferation, cytokine production,

and cytolytic activity, leading to the functional inactivation or

exhaustion of T cells. PD-L1 also binds with CD80 on antigen

presenting cells and activated T cells mediating downregulation

of immune responses, including inhibition of T-cell activation

and cytokine production. PD-L1 expression is observed in

immune cells and TC.  Aberrant expression of PD-L1 on TC

has been reported to impede anti-tumor immunity, resulting in

immune evasion.  The emergence of immunotherapies that

interrupt the PD-L1 / PD-1 pathway have been shown to improve

survival rates for patients diagnosed with NSCLC. However,

prognosis with treatment is dependent on the level of PD-L1

expression and therefore requires quantiﬁcation of PD-L1 with

immunohistochemical staining.

Immunohistochemistry can be used to detect speciﬁc antigens

present in tissue samples, making it an effective tool for

pathologists in their diagnosis and prognosis of carcinomas. The

VENTANA PD-L1 (SP 263) Assay is a rabbit monoclonal antibody

intended for laboratory use for the semi-quantitative detection

of PD-L1 protein in sections of FFPE normal and neoplastic

tissue. An advantage of histological tissue preparations is that

intact tissue allows morphology to aid in the interpretation of

the PD-L1 positivity of the patient sample. All histological tests

should be interpreted by a specialist in NSCLC morphology,

and/or pathology. The results should be complemented by

morphological studies, proper controls and used in conjunction

with other clinical and laboratory data.

4 uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide

Test Principles

The uPath enterprise software with the uPath PD-L1 (SP263)

image analysis for NSCLC algorithm employs image analysis

techniques to obtain a TC Positivity score.

The uPath PD-L1 (SP263) image analysis for NSCLC algorithm

uses pre-deﬁned parameters to score images of tissue stained

with the VENTANA PD-L1 (SP263) Assay.

Steps involved in image analysis:

• Identiﬁcation of white space and automatic exclusion from

analysis.

• Detection of cells across the entire image.

• Classiﬁcation of cells as TC or other cell types.

• Identiﬁcation of stained versus unstained TC.

• Computation of the TC Positivity score by dividing the number of

stained TC by the total number of TC according to the VENTANA

PD-L1 (SP263) Assay method sheet.

How uPath PD-L1 (SP263) image analysis for NSCLC

algorithm identiﬁes TC and how the score is calculated:

• The uPath PD-L1 (SP263) image analysis for NSCLC algorithm

identiﬁes TC using color, intensity, size and morphological

features.

• Identiﬁed TC are classiﬁed as stained using detected membrane

and pre-set thresholds that are in line with the VENTANA PD-L1

(SP263) Assay method sheet.

• To calculate the percentage of stained TC, the number of

stained TC is divided by the total number of TC according to the

VENTANA PD-L1 (SP263) Assay method sheet.

uPath PD-L1 (SP263) image analysis for NSCLC algorithm

white space determination:

• The algorithm will automatically exclude white space. Artifacts

such as dirt, scratches or ink may not be automatically excluded.

• The user may review the areas determined by the algorithm to

be white space using a false color overlay; see “PD-L1 Image

Analysis: False Color Overlay”.

The uPath PD-L1 (SP263) image analysis for NSCLC

algorithm’s criteria for generating the TC positivity score

output:

• The uPath PD-L1 (SP263) image analysis for NSCLC algorithm

will report out a score to one digit in the tenths place, e.g. “4.8%”.

• It is not recommended to round the score up or down. For

example, “4.8%” should not be rounded up to 5%.

uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide 5

The uPath PD-L1 (SP263) image analysis for NSCLC algorithm is

designed to work for VENTANA PD-L1 (SP263) Assay. The test

results are only as good as the quality and accuracy of the IHC

slide that is imaged, and the subsequent image that is analyzed.

The pathologist must validate the VENTANA PD-L1 (SP263)

Assay staining run by manual microscopic examination of the

PD-L1 control slides to verify that the expected results have been

obtained before images of slides are accessioned onto the uPath

enterprise software for analysis.

Use the manufacturer's recommendations for the VENTANA

PD-L1 (SP263) Assay, including all positive and negative quality

control materials for each staining run. If the control slides are

not acceptable with manual microscopic examination, restain the

tissue with acceptable results.

The pathologist must follow the recommendations for VENTANA

PD-L1 (SP263) Assay interpretation.

Refer to the VENTANA PD-L1 (SP263) Assay method sheet (P/N

1014258EN) and interpretation guide (P/N 1015317EN) (available

at www.ventana.com).

The uPath PD-L1 (SP263) image analysis for NSCLC algorithm

is designed for use by a qualiﬁed pathologist in conjunction

with histological examination, relevant clinical information, and

proper controls. It is not designed to be a standalone tool, and

requires competent human intervention throughout the analysis

process.

The uPath PD-L1 (SP263) image analysis for NSCLC algorithm

may generate incorrect scores if the captured images have

abnormal staining (nuclear, cytoplasm, etc.).

The uPath PD-L1 (SP263) image analysis for NSCLC algorithm

will reject tumor nuclei that are elongated regardless of the

overall shape of the cell. For this reason, tumors containing large

numbers of cells with elongated nuclei may need to be evaluated

manually.

Limitations

The uPath PD-L1 (SP263) image analysis for NSCLC algorithm

has been trained, developed, and validated on NSCLC tissue

samples.

The uPath PD-L1 (SP263) image analysis for NSCLC algorithm

has not been tested, or its safety and effectiveness validated,

when used with a personal computer (PC) from home.

The uPath PD-L1 SP263 image analysis algorithm is indicated for

use as an aid in identifying patients with NSCLC for treatment

with therapies with the 50% PD-L1 TC positivity cutoff in

accordance with the approved therapeutic product labeling.

The uPath PD-L1 (SP263) image analysis for NSCLC algorithm

may misidentify cells due to the presence of weak cytoplasmic

and/or membranous staining, strong immune cell staining

overlapping with tumor cell staining where there is signiﬁcant

intermixed inﬂammation, TC with cytoplasmic blush, and non-

target staining. This may result in misidentiﬁcation of TC as non-

TC, and of non-TC as positive TC.

Although it is required for macrophages to be excluded from

the region of analysis, it is not always possible to exclude all

macrophages. As a result, the score generated by the uPath

PD-L1 (SP263) image analysis for NSCLC algorithm may be

inﬂuenced by the macrophages in the ROI being analyzed. This is

critical when a patient score is close to the cutoff of 50%.

Cytoplasmic staining is generally diffuse with some cases

displaying a ﬁne granular quality. Rare cases have shown a

perinuclear dot-like body staining with variable intensity. The

total percentage of tumor membrane signal intensities is visually

estimated and used to generate the PD-L1 expression level.

Tumor cell cytoplasmic staining is disregarded for determining

PD-L1 expression. An isotype matched negative control antibody

is used to evaluate the presence of background in test samples

and establish a staining intensity baseline.

6 uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide

Data Security

Malicious software or unauthorized instrument access can result

in data loss or instrument unavailability.

To avoid infection by malicious software or unauthorized access

and misuse of the instrument, the following recommendations

are essential:

• Do not install or run any other software on the instrument.

• Make sure that other computers and services on the network

are properly secured and protected against malicious software

and unauthorized access. For example, the laboratory

information system (LIS), archiving share, backup share, or

service.

• Customers are responsible for the security of their local area

network, especially in protecting it against malicious software

and attacks. This protection might include measures, such as

a ﬁrewall, to separate the device from uncontrolled networks.

This protection might also include measures that ensure that the

connected network is free of malicious code.

• Restrict physical access to the instrument and all attached IT

infrastructure (computers, cables, network equipment, and so

on).

• Make sure that instrument backup and archive ﬁles are

protected from any unauthorized access and disaster. This list

includes the remote storage location, disaster discovery sites,

and the secure transfer of backup ﬁles.

• If possible, use a ﬁrewall to restrict network trafﬁc.

• USB ﬂash drives can be used for several kinds of backups and

restores. Wrong handling of a USB ﬂash drive may result in data

loss or malfunction of the instrument.

• Use only USB ﬂash drives that are tested and installed by your

local Roche service representative.

• At any one time only one USB device can be in use. Before

inserting a USB ﬂash drive, check that no other USB device is

inserted.

• Before removing a USB ﬂash drive, choose the Eject button in

Windows.

• The default operating system (OS) conﬁguration provided with

the server should not be altered as this has implications on the

hardened OS conﬁgurations.

• To prevent a virus from infecting the uPath enterprise software,

use the USB ﬂash drive exclusively on the instrument. Do not

store other data on this USB ﬂash drive.

uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide 7

Workﬂow for using the uPath PD-L1 image analysis for NSCLC Algorithm

Materials needed

• uPath enterprise software

• uPath PD-L1 (SP263) image analysis for NSCLC algorithm

• NSCLC tissue slides stained with the VENTANA PD-L1 (SP263) Assay (using OptiView DAB IHC Detection Kit) on the BenchMark

ULTRA instrument

• VENTANA DP 200 slide scanner

Workﬂow

1. An NSCLC tissue sample on a glass slide is stained with the VENTANA PD-L1 (SP263) Assay using a BenchMark ULTRA instrument.

2. Image acquisition (whole slide scanning) is performed with the VENTANA DP 200 slide scanner at 20x magniﬁcation at one z-plane.

3. Once digital images are acquired, these images are transferred from the computer associated with the VENTANA DP 200 slide scanner

to the image management system (IMS) on a centralized server.

4. Following transfer to the server, a case will be created in the uPath enterprise software. Case creation can occur automatically through

communication with the laboratory information system (LIS) using identiﬁcation information (i.e., tissue type and primary antibody)

contained in the barcode label of the glass slide or entered manually into the uPath enterprise software (refer to the uPath enterprise

software User Guide (PN 1018943EN)).

5. If the uPath PD-L1 (SP263) image analysis for NSCLC algorithm is installed (must be installed on a separate server from the uPath

enterprise software and the IMS) and a 20x image is accessioned with the appropriate stain and tissue type, the uPath enterprise

software then automatically triggers Whole Slide Analysis (WSA).

6. WSA automatically analyzes the entire scanned image.

7. Once WSA is completed, the pathologist is notiﬁed within the uPath enterprise software that “analysis is complete.” The pathologist is

now able to select speciﬁc ROIs to score. A pathologist may select a single ROI of any size or multiple ROIs. If multiple ROIs are selected,

an aggregate score is provided as well as an individual score for each ROI.

Staining

• Tissue preparation and staining should follow the recommendations provided in the VENTANA PD-L1 (SP263) Assay method sheet.

• All proper controls should be reviewed and slides should be restained if the staining does not meet the guidelines outlined in the

VENTANA PD-L1 (SP263) Assay method sheet.

• The uPath PD-L1 (SP263) image analysis for NSCLC algorithm requires use of the VENTANA PD-L1 (SP263) Assay, and any additional

material or supplies listed in the VENTANA PD-L1 (SP263) Assay method sheet, to stain tissues prior to analysis. The VENTANA PD-L1

(SP263) Assay detects PD-L1 protein in FFPE NSCLC tissue stained with the OptiView DAB IHC Detection Kit on a BenchMark ULTRA

instrument. Though the VENTANA PD-L1 (SP263) Assay detects PD-L1 protein in FFPE NSCLC tissue stained on thee BenchMark

ULTRA instruments, the uPath PD-L1 (SP263) image analysis for NSCLC algorithm was validated using the OptiView DAB IHC

Detection Kit stained on the BenchMark ULTRA instrument.

Image Capture

The VENTANA DP 200 slide scanner is required for scanning of the slides. Images are required to be scanned at 20x magniﬁcation.

If large sections of the image are out of focus, it s recommended that the slides be rescanned. For further information on scanning,

please refer to the VENTANA DP 200 slide scanner User Manual (PN 1017149EN).

General Navigation: uPath enterprise software

The uPath enterprise software is meant to be customizable to individual and site needs including but not limited to: report

conﬁguration and user interface. This Algorithm Guide will focus on the tools necessary for using the uPath PD-L1 (SP263) image

analysis for NSCLC algorithm only. For further information on the uPath enterprise software, please refer to the uPath enterprise

software User Guide.

8 uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide

Pathologist Workﬂow

Opening a Case

Images of NSCLC tissue stained with the VENTANA PD-L1 (SP263) Assay can be accessed by double-clicking on a case or by

selecting a case and pressing the viewer tab within uPath enterprise software (Figure 1).

A screen with all images associated with a case will appear (Figure 2).

Figure 2

Figure 1

uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide 9

Once a glass slide stained with the VENTANA PD-L1 (SP263) Assay is scanned on a VENTANA DP 200 slide scanner at 20x, the

image is imported into the uPath enterprise software and associated with a case. The uPath PD-L1 (SP263) image analysis for NSCLC

algorithm will automatically trigger WSA. Times to complete the WSA precomputing step depend on server speciﬁcations, image sizes

and number of images in the queue. When displayed, “waiting to start auto-analysis” speciﬁes the images are in queue and yet to be

analyzed and “analyzing” is used when WSA is being performed (Figures 3 and 4). Once the image is completely analyzed via WSA

in the uPath enterprise software, “analysis successful” will be displayed underneath the slide image within the viewer in the uPath

enterprise software (Figure 5). Images cannot be scored prior to successful WSA completion.

Drawing Whole Tumor ROI(s): Selecting Tumor Area

Use the Freehand tool button within the ROI dropdown menu (Figure 6) to select the tumor area(s) on the IHC slide image to be

analyzed. Figure 7 illustrates an image that has a single ROI drawn. Additional ROIs can be drawn. Each area selected will cause an

ROI to appear in the Slide Panel (Figure 8).

Figure 6 Figure 7

Figure 8

Figure 5

Figure 4

Figure 3

10 uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide

Drawing Whole Tumor ROI(s): Exclusion Area

When drawing the ROIs, the exclusion of certain areas may be required; speciﬁc areas to be avoided or omitted as well as examples

will be addressed within the staining characteristics section below. Use the Freehand exclusion tool within the Exclusion dropdown

menu (Figure 9) to exclude speciﬁc areas (Figure 10). If large areas of the image are blurry or out of focus, rescan the slide.

Excluded areas will not be analyzed by the algorithm, and the stained and unstained TC within this area will be excluded from the total

analysis area. If the ROI has already been analyzed, and an exclusion is used, the ROI will need to be reanalyzed and the overlay and

score will be updated appropriately.

Drawing a high number of exclusions, especially complicated Freehand exclusions, can be time consuming and impact workﬂow

efﬁciency with only a marginal impact on the ﬁnal score. If a case requires a high number of exclusions, the pathologist should do the

following:

• Draw multiple ROIs and exclude portions of tissue they deem unscorable with minimal use of the Exclusion tool.

• Limit exclusions and manually override the score with another score.

Drawing Whole Tumor ROI(s): Deletion

If a selected whole tumor ROI is not optimal, it can be deleted. Select the whole tumor ROI by clicking on the center of the ROI on

the image and then clicking the Delete button within the Slide Panel (Figure 11) or within the slide image near the ROI (Figure 12). A

conﬁrmation window will appear. Select Conﬁrm to delete the selected ROI. Select Cancel to retain the ROI.

Figure 10Figure 9

Figure 11 Figure 12

uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide 11

Once all whole tumor ROI(s) and/or exclusion areas have been drawn, the image is ready to be analyzed. Select the whole tumor ROI by

clicking on the center of the ROI to be analyzed or clicking on the ROI in the Slide Panel. For each ROI, select the Image Analysis button

either within the Slide Panel (Figure 13) or next to the ROI (Figure 14).

Once the PD-L1 Analysis is complete, the result will appear in the Slide Panel in two locations: under Slide Score and next to the ROIs

(Figure 15). The Slide Score is based on a summation of the tumor cell positivity status across all selected ROI(s), which is the score

that will appear in the report.

PD-L1 Image Analysis

Figure 15

You can also see more detailed information in the Slide Score ﬂip-out and the ROI Details ﬂip-out by clicking the ﬂip-out icon (Figure

16). The Slide Score ﬂip-out will appear (Figure 17). Clicking the same ﬂip-out icon will also hide this information.

Figure 17

Figure 16

Figure 13 Figure 14

12 uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide

PD-L1 Image Analysis: False Color Overlay

Once the ROI(s) Analysis button has been pressed and the tissue analyzed, a color overlay will be displayed on the ROI. In the image

below (Figure 18), the red circles represent cells determined to be positively stained for PD-L1 and blue circles represent cells

determined to be negative for PD-L1. When grabbing the image (left-clicking with the mouse and moving the image) the overlay will

disappear (Figure 19). When the mouse button released, the overlay reappears (Figure 18).

Figure 18

Figure 19

uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide 13

Manual Override Slide Score Entry

Scores can be manually overridden by clicking on the Slide Score ﬂip-out icon within the Slide Panel next to the Slide Score (Figure

16). The Slide Score ﬂip-out will appear (Figure 20). Selecting the edit button (Figure 20) on the Slide Score ﬂip-out allows the user to

type in a manual score (Figure 21). The Comments ﬁeld allows notes regarding the case and/or decision to override the automated

score. For PD-L1, scores of 0-100% may be manually entered. Upon entry of a Manual Override score, select the conﬁrm notiﬁcation

(Figure 22). A conﬁrmation message will appear, select “Yes”.

The score within the Slide Panel will now reﬂect the manual override score. The image analysis score provided next to the ROI(s) will no

longer be present (Figure 23). The user will have the option to re-analyze the image by pressing the bar graph button (Figure 13, Figure

14).

Figure 21 Figure 22

Figure 20

Figure 23

14 uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide

Please see the VENTANA PD-L1 (SP263) Assay method sheet and Interpretation Guide.

PD-L1 Evaluation

NSCLC neoplastic cells labeled with the VENTANA PD-L1 (SP263) Assay are evaluated for percent positivity of the TC with membrane

staining at any intensity. The immunohistochemical staining in NSCLC is membranous and/or cytoplasmic, and may be expressed

homogeneously or heterogeneously throughout the neoplasm. Tumor cell cytoplasmic staining is not factored into the TC positivity

score. Membrane staining can have a discontinuous, circumferential or basolateral pattern. An isotype-matched negative control

antibody is used to evaluate the presence of background in test samples.

PD-L1 Algorithm Stain Evaluation

The pathologist using the uPath PD-L1 (SP263) image analysis for NSCLC algorithm should be familiar with manually scoring the

VENTANA PD-L1 (SP263) Assay. The pathologist should use the freehand tool to circle the whole tumor area. The pathologist should

reference the associated H&E and negative control slide prior to using the uPath PD-L1 (SP263) image analysis for NSCLC algorithm.

When selecting the areas to be analyzed, please take into consideration the limitations described in the Limitations and the Areas to

avoid sections. If the pathologist disagrees with the score provided by the uPath PD-L1 (SP263) image analysis for NSCLC algorithm,

the pathologist should manually override the score.

Non-evaluable cases include, but are not limited to, cases with insufﬁcient viable tumor, unacceptable morphology, and interfering

background. NSCLC cases with sufﬁcient viable TC (as determined by the scoring pathologist) and no interfering background on the

PD-L1 IHC slide are acceptable for evaluation.

Staining Characteristics

uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide 15

Figure 24: Scanned images of IHC stained NSCLC tissue in uPath enterprise software; before analysis (above) and after

analysis (below). The red overlay represents cells determined to be positively stained TC and blue overlay represents cells

determined to be negatively stained TC.

Images of various staining patterns and PD-L1 expression levels are provided in the subsequent ﬁgures (24-25). PD-L1 expression in

TC is reported as a percentage (0-100).

16 uPath PD-L1 (SP263) image analysis for Non-Small Cell Lung Cancer (NSCLC) Algorithm Guide

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